-----------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\afang\Documents\PSRM_BallotSecrecy\PublicReplicationArchive\03_Appendix.log
  log type:  text
 opened on:  31 Mar 2017, 14:47:57

. /*----------------------------------------------------------------------
>  
>  REPLICATION FILE FOR
>  Gerber, Alan S., Gregory A. Huber, Albert H. Fang, and Andrew Gooch. (Forthcoming)
>  "Non-Governmental Campaign Communication Providing Ballot Secrecy Assurances Increases
>    Turnout: Results from Two Large Scale Experiments"
>  Political Science Research and Methods
>  
>  FILE:                  03_Appendix.do
>  DESCRIPTION:   Performs analysis reported in tables/figures in supplemental appendix
>  DATE:                  14 Dec 2016
>  VERSION:               1.0
> 
> ----------------------------------------------------------------------*/
. use PublicReplicationData, clear

. 
. /*-----------------------
> TABLES A1 TO A2:
> Subjects by State, Arm
> Among Registered Never-Voters
>         A1: 6-Arm Coding
>         A2: 3-Arm Coding
> -----------------------*/
. 
. foreach t in t6 t3 {
  2. foreach u in 1 0 {
  3. 
.         if (`u'==1){
  4.                 local ulab = "under55"
  5.                 local subp = "A"
  6.         }
  7.         else {
  8.                 local ulab = "over55"
  9.                 local subp = "B"
 10.         }
 11.         
.         if ( "`t'" == "t6" ) {
 12.         
.                 * HOUSEHOLDS
.                 preserve
 13.                 keep if under55==`u' & never_voted==1 & flag_hh_mixed_nv!=1
 14.                 duplicates drop hhid, force
 15.                 tabout `t' state using "TableA1_DistByStateByArm_NeverVoters_Panel1HH_SubPanel`s
> ubp'.xls", cells(freq col) replace
 16.                 restore 
 17.                 * SUBJECTS
.                 preserve
 18.                 keep if under55==`u' & never_voted==1 & flag_hh_mixed_nv!=1
 19.                 tabout `t' state using "TableA1_DistByStateByArm_NeverVoters_Panel2Subj_SubPanel
> `subp'.xls", cells(freq col) replace
 20.                 restore
 21. 
.         }
 22.         else {
 23.         
.                 * HOUSEHOLDS
.                 preserve
 24.                 keep if under55==`u' & never_voted==1 & flag_hh_mixed_nv!=1
 25.                 duplicates drop hhid, force
 26.                 tabout `t' state using "TableA2_DistByStateByArm_NeverVoters_Panel1HH_SubPanel`s
> ubp'.xls", cells(freq col) replace
 27.                 restore 
 28.                 * SUBJECTS
.                 preserve
 29.                 keep if under55==`u' & never_voted==1 & flag_hh_mixed_nv!=1
 30.                 tabout `t' state using "TableA2_DistByStateByArm_NeverVoters_Panel2Subj_SubPanel
> `subp'.xls", cells(freq col) replace
 31.                 restore
 32. 
. 
.         }
 33. 
. }
 34. }
(33,387 observations deleted)

Duplicates in terms of hhid

(11,584 observations deleted)

Table output written to: TableA1_DistByStateByArm_NeverVoters_Panel1HH_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,206.0 9.1     3,202.0 9.1     1,120.0 9.1     3,472.0 9.1     2,663.0 9.1     11,91
> 0.0        9.1     24,573.0        9.1
1: sticker      4,408.0 18.2    6,393.0 18.2    2,246.0 18.2    6,944.0 18.2    5,328.0 18.2    23,82
> 9.0        18.2    49,148.0        18.2
2: ballot secrecy       4,410.0 18.2    6,400.0 18.2    2,242.0 18.2    6,946.0 18.2    5,330.0 18.2 
>    23,842.0        18.2    49,170.0        18.2
3: disappoint   4,410.0 18.2    6,401.0 18.2    2,242.0 18.2    6,946.0 18.2    5,332.0 18.2    23,82
> 7.0        18.2    49,158.0        18.2
4: PURL 4,409.0 18.2    6,400.0 18.2    2,241.0 18.2    6,938.0 18.2    5,326.0 18.2    23,819.0     
>    18.2    49,133.0        18.2
5: PURL + postcard      4,413.0 18.2    6,401.0 18.2    2,244.0 18.2    6,944.0 18.2    5,328.0 18.2 
>    23,833.0        18.2    49,163.0        18.2
Total   24,256.0        100.0   35,197.0        100.0   12,335.0        100.0   38,190.0        100.0
>    29,307.0        100.0   131,060.0       100.0   270,345.0       100.0
(33,387 observations deleted)

Table output written to: TableA1_DistByStateByArm_NeverVoters_Panel2Subj_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,301.0 9.1     3,326.0 9.1     1,150.0 9.0     3,620.0 9.1     2,756.0 9.1     12,51
> 0.0        9.1     25,663.0        9.1
1: sticker      4,576.0 18.1    6,634.0 18.2    2,311.0 18.2    7,254.0 18.3    5,470.0 18.1    24,96
> 6.0        18.2    51,211.0        18.2
2: ballot secrecy       4,600.0 18.2    6,645.0 18.2    2,314.0 18.2    7,214.0 18.2    5,497.0 18.1 
>    25,008.0        18.2    51,278.0        18.2
3: disappoint   4,591.0 18.2    6,633.0 18.2    2,315.0 18.2    7,207.0 18.1    5,537.0 18.3    24,93
> 9.0        18.1    51,222.0        18.2
4: PURL 4,573.0 18.1    6,608.0 18.1    2,308.0 18.1    7,211.0 18.2    5,509.0 18.2    25,033.0     
>    18.2    51,242.0        18.2
5: PURL + postcard      4,582.0 18.2    6,657.0 18.2    2,321.0 18.2    7,205.0 18.1    5,534.0 18.3 
>    25,014.0        18.2    51,313.0        18.2
Total   25,223.0        100.0   36,503.0        100.0   12,719.0        100.0   39,711.0        100.0
>    30,303.0        100.0   137,470.0       100.0   281,929.0       100.0
(282,338 observations deleted)

Duplicates in terms of hhid

(901 observations deleted)

Table output written to: TableA1_DistByStateByArm_NeverVoters_Panel1HH_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      247.0   10.0    494.0   10.0    174.0   10.2    341.0   10.0    306.0   10.0    1,648
> .0 10.0    3,210.0 10.0
1: sticker      2,216.0 90.0    4,443.0 90.0    1,527.0 89.8    3,074.0 90.0    2,760.0 90.0    14,84
> 7.0        90.0    28,867.0        90.0
Total   2,463.0 100.0   4,937.0 100.0   1,701.0 100.0   3,415.0 100.0   3,066.0 100.0   16,495.0     
>    100.0   32,077.0        100.0
(282,338 observations deleted)

Table output written to: TableA1_DistByStateByArm_NeverVoters_Panel2Subj_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      250.0   10.0    501.0   9.8     178.0   10.2    347.0   10.0    313.0   9.9     1,701
> .0 10.0    3,290.0 10.0
1: sticker      2,255.0 90.0    4,590.0 90.2    1,568.0 89.8    3,121.0 90.0    2,833.0 90.1    15,32
> 1.0        90.0    29,688.0        90.0
Total   2,505.0 100.0   5,091.0 100.0   1,746.0 100.0   3,468.0 100.0   3,146.0 100.0   17,022.0     
>    100.0   32,978.0        100.0
(33,387 observations deleted)

Duplicates in terms of hhid

(11,584 observations deleted)

Table output written to: TableA2_DistByStateByArm_NeverVoters_Panel1HH_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,206.0 9.1     3,202.0 9.1     1,120.0 9.1     3,472.0 9.1     2,663.0 9.1     11,91
> 0.0        9.1     24,573.0        9.1
1: ballot secrecy       13,228.0        54.5    19,194.0        54.5    6,730.0 54.6    20,836.0     
>    54.6    15,990.0        54.6    71,498.0        54.6    147,476.0       54.6
2: personalized url     8,822.0 36.4    12,801.0        36.4    4,485.0 36.4    13,882.0        36.3 
>    10,654.0        36.4    47,652.0        36.4    98,296.0        36.4
Total   24,256.0        100.0   35,197.0        100.0   12,335.0        100.0   38,190.0        100.0
>    29,307.0        100.0   131,060.0       100.0   270,345.0       100.0
(33,387 observations deleted)

Table output written to: TableA2_DistByStateByArm_NeverVoters_Panel2Subj_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,301.0 9.1     3,326.0 9.1     1,150.0 9.0     3,620.0 9.1     2,756.0 9.1     12,51
> 0.0        9.1     25,663.0        9.1
1: ballot secrecy       13,767.0        54.6    19,912.0        54.5    6,940.0 54.6    21,675.0     
>    54.6    16,504.0        54.5    74,913.0        54.5    153,711.0       54.5
2: personalized url     9,155.0 36.3    13,265.0        36.3    4,629.0 36.4    14,416.0        36.3 
>    11,043.0        36.4    50,047.0        36.4    102,555.0       36.4
Total   25,223.0        100.0   36,503.0        100.0   12,719.0        100.0   39,711.0        100.0
>    30,303.0        100.0   137,470.0       100.0   281,929.0       100.0
(282,338 observations deleted)

Duplicates in terms of hhid

(901 observations deleted)

Table output written to: TableA2_DistByStateByArm_NeverVoters_Panel1HH_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      247.0   10.0    494.0   10.0    174.0   10.2    341.0   10.0    306.0   10.0    1,648
> .0 10.0    3,210.0 10.0
1: ballot secrecy       2,216.0 90.0    4,443.0 90.0    1,527.0 89.8    3,074.0 90.0    2,760.0 90.0 
>    14,847.0        90.0    28,867.0        90.0
Total   2,463.0 100.0   4,937.0 100.0   1,701.0 100.0   3,415.0 100.0   3,066.0 100.0   16,495.0     
>    100.0   32,077.0        100.0
(282,338 observations deleted)

Table output written to: TableA2_DistByStateByArm_NeverVoters_Panel2Subj_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      250.0   10.0    501.0   9.8     178.0   10.2    347.0   10.0    313.0   9.9     1,701
> .0 10.0    3,290.0 10.0
1: ballot secrecy       2,255.0 90.0    4,590.0 90.2    1,568.0 89.8    3,121.0 90.0    2,833.0 90.1 
>    15,321.0        90.0    29,688.0        90.0
Total   2,505.0 100.0   5,091.0 100.0   1,746.0 100.0   3,468.0 100.0   3,146.0 100.0   17,022.0     
>    100.0   32,978.0        100.0

. 
. /*-----------------------
> TABLES A3 TO A4:
> Subjects by State, Arm
> Among Full Sample
>         A3: 6-Arm Coding
>         A4: 3-Arm Coding
> -----------------------*/
. 
. foreach t in t6 t3 {
  2. foreach u in 1 0 {
  3. 
.         if (`u'==1){
  4.                 local ulab = "under55"
  5.                 local subp = "A"
  6.         }
  7.         else {
  8.                 local ulab = "over55"
  9.                 local subp = "B"
 10.         }
 11.         
.         if ( "`t'" == "t6" ) {
 12.         
.                 * HOUSEHOLDS
.                 preserve
 13.                 keep if under55==`u'
 14.                 duplicates drop hhid, force
 15.                 tabout `t' state using "TableA3_DistByStateByArm_FullSample_Panel1HH_SubPanel`su
> bp'.xls", cells(freq col) replace
 16.                 restore 
 17.                 * SUBJECTS
.                 preserve
 18.                 keep if under55==`u'
 19.                 tabout `t' state using "TableA3_DistByStateByArm_FullSample_Panel2Subj_SubPanel`
> subp'.xls", cells(freq col) replace
 20.                 restore
 21. 
.         }
 22.         else {
 23.         
.                 * HOUSEHOLDS
.                 preserve
 24.                 keep if under55==`u'
 25.                 duplicates drop hhid, force
 26.                 tabout `t' state using "TableA4_DistByStateByArm_FullSample_Panel1HH_SubPanel`su
> bp'.xls", cells(freq col) replace
 27.                 restore 
 28.                 * SUBJECTS
.                 preserve
 29.                 keep if under55==`u'
 30.                 tabout `t' state using "TableA4_DistByStateByArm_FullSample_Panel2Subj_SubPanel`
> subp'.xls", cells(freq col) replace
 31.                 restore
 32. 
. 
.         }
 33. 
. }
 34. }
(33,071 observations deleted)

Duplicates in terms of hhid

(11,598 observations deleted)

Table output written to: TableA3_DistByStateByArm_FullSample_Panel1HH_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,206.0 9.1     3,202.0 9.1     1,123.0 9.1     3,473.0 9.1     2,664.0 9.1     11,93
> 2.0        9.1     24,600.0        9.1
1: sticker      4,409.0 18.2    6,401.0 18.2    2,247.0 18.2    6,947.0 18.2    5,329.0 18.2    23,87
> 8.0        18.2    49,211.0        18.2
2: ballot secrecy       4,410.0 18.2    6,401.0 18.2    2,243.0 18.2    6,946.0 18.2    5,330.0 18.2 
>    23,881.0        18.2    49,211.0        18.2
3: disappoint   4,410.0 18.2    6,403.0 18.2    2,245.0 18.2    6,947.0 18.2    5,333.0 18.2    23,87
> 1.0        18.2    49,209.0        18.2
4: PURL 4,409.0 18.2    6,403.0 18.2    2,243.0 18.2    6,948.0 18.2    5,328.0 18.2    23,871.0     
>    18.2    49,202.0        18.2
5: PURL + postcard      4,413.0 18.2    6,402.0 18.2    2,245.0 18.2    6,949.0 18.2    5,328.0 18.2 
>    23,877.0        18.2    49,214.0        18.2
Total   24,257.0        100.0   35,212.0        100.0   12,346.0        100.0   38,210.0        100.0
>    29,312.0        100.0   131,310.0       100.0   270,647.0       100.0
(33,071 observations deleted)

Table output written to: TableA3_DistByStateByArm_FullSample_Panel2Subj_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,301.0 9.1     3,326.0 9.1     1,153.0 9.1     3,621.0 9.1     2,757.0 9.1     12,53
> 2.0        9.1     25,690.0        9.1
1: sticker      4,577.0 18.1    6,642.0 18.2    2,312.0 18.2    7,257.0 18.3    5,471.0 18.1    25,01
> 6.0        18.2    51,275.0        18.2
2: ballot secrecy       4,600.0 18.2    6,646.0 18.2    2,315.0 18.2    7,214.0 18.2    5,497.0 18.1 
>    25,052.0        18.2    51,324.0        18.2
3: disappoint   4,591.0 18.2    6,635.0 18.2    2,318.0 18.2    7,208.0 18.1    5,539.0 18.3    24,98
> 4.0        18.1    51,275.0        18.2
4: PURL 4,573.0 18.1    6,611.0 18.1    2,310.0 18.1    7,221.0 18.2    5,511.0 18.2    25,088.0     
>    18.2    51,314.0        18.2
5: PURL + postcard      4,582.0 18.2    6,658.0 18.2    2,322.0 18.2    7,211.0 18.1    5,534.0 18.3 
>    25,060.0        18.2    51,367.0        18.2
Total   25,224.0        100.0   36,518.0        100.0   12,730.0        100.0   39,732.0        100.0
>    30,309.0        100.0   137,732.0       100.0   282,245.0       100.0
(282,245 observations deleted)

Duplicates in terms of hhid

(903 observations deleted)

Table output written to: TableA3_DistByStateByArm_FullSample_Panel1HH_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      247.0   10.0    495.0   10.0    175.0   10.3    341.0   10.0    306.0   10.0    1,654
> .0 10.0    3,218.0 10.0
1: sticker      2,216.0 90.0    4,446.0 90.0    1,531.0 89.7    3,080.0 90.0    2,766.0 90.0    14,91
> 1.0        90.0    28,950.0        90.0
Total   2,463.0 100.0   4,941.0 100.0   1,706.0 100.0   3,421.0 100.0   3,072.0 100.0   16,565.0     
>    100.0   32,168.0        100.0
(282,245 observations deleted)

Table output written to: TableA3_DistByStateByArm_FullSample_Panel2Subj_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 6-arm (original coding)  AR      AR      GA      GA      LA      LA      MI      MI   
>    NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      250.0   10.0    502.0   9.9     179.0   10.2    347.0   10.0    313.0   9.9     1,707
> .0 10.0    3,298.0 10.0
1: sticker      2,255.0 90.0    4,593.0 90.1    1,573.0 89.8    3,127.0 90.0    2,839.0 90.1    15,38
> 6.0        90.0    29,773.0        90.0
Total   2,505.0 100.0   5,095.0 100.0   1,752.0 100.0   3,474.0 100.0   3,152.0 100.0   17,093.0     
>    100.0   33,071.0        100.0
(33,071 observations deleted)

Duplicates in terms of hhid

(11,598 observations deleted)

Table output written to: TableA4_DistByStateByArm_FullSample_Panel1HH_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,206.0 9.1     3,202.0 9.1     1,123.0 9.1     3,473.0 9.1     2,664.0 9.1     11,93
> 2.0        9.1     24,600.0        9.1
1: ballot secrecy       13,229.0        54.5    19,205.0        54.5    6,735.0 54.6    20,840.0     
>    54.5    15,992.0        54.6    71,630.0        54.6    147,631.0       54.5
2: personalized url     8,822.0 36.4    12,805.0        36.4    4,488.0 36.4    13,897.0        36.4 
>    10,656.0        36.4    47,748.0        36.4    98,416.0        36.4
Total   24,257.0        100.0   35,212.0        100.0   12,346.0        100.0   38,210.0        100.0
>    29,312.0        100.0   131,310.0       100.0   270,647.0       100.0
(33,071 observations deleted)

Table output written to: TableA4_DistByStateByArm_FullSample_Panel2Subj_SubPanelA.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      2,301.0 9.1     3,326.0 9.1     1,153.0 9.1     3,621.0 9.1     2,757.0 9.1     12,53
> 2.0        9.1     25,690.0        9.1
1: ballot secrecy       13,768.0        54.6    19,923.0        54.6    6,945.0 54.6    21,679.0     
>    54.6    16,507.0        54.5    75,052.0        54.5    153,874.0       54.5
2: personalized url     9,155.0 36.3    13,269.0        36.3    4,632.0 36.4    14,432.0        36.3 
>    11,045.0        36.4    50,148.0        36.4    102,681.0       36.4
Total   25,224.0        100.0   36,518.0        100.0   12,730.0        100.0   39,732.0        100.0
>    30,309.0        100.0   137,732.0       100.0   282,245.0       100.0
(282,245 observations deleted)

Duplicates in terms of hhid

(903 observations deleted)

Table output written to: TableA4_DistByStateByArm_FullSample_Panel1HH_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      247.0   10.0    495.0   10.0    175.0   10.3    341.0   10.0    306.0   10.0    1,654
> .0 10.0    3,218.0 10.0
1: ballot secrecy       2,216.0 90.0    4,446.0 90.0    1,531.0 89.7    3,080.0 90.0    2,766.0 90.0 
>    14,911.0        90.0    28,950.0        90.0
Total   2,463.0 100.0   4,941.0 100.0   1,706.0 100.0   3,421.0 100.0   3,072.0 100.0   16,565.0     
>    100.0   32,168.0        100.0
(282,245 observations deleted)

Table output written to: TableA4_DistByStateByArm_FullSample_Panel2Subj_SubPanelB.xls

        State                                                                                        
>            
Treatment Arm: 3-arm (pool ballot secrecy, pool PURL)   AR      AR      GA      GA      LA      LA   
>    MI      MI      NC      NC      TX      TX      Total   Total
        No.     %       No.     %       No.     %       No.     %       No.     %       No.     %    
>    No.     %
0: control      250.0   10.0    502.0   9.9     179.0   10.2    347.0   10.0    313.0   9.9     1,707
> .0 10.0    3,298.0 10.0
1: ballot secrecy       2,255.0 90.0    4,593.0 90.1    1,573.0 89.8    3,127.0 90.0    2,839.0 90.1 
>    15,386.0        90.0    29,773.0        90.0
Total   2,505.0 100.0   5,095.0 100.0   1,752.0 100.0   3,474.0 100.0   3,152.0 100.0   17,093.0     
>    100.0   33,071.0        100.0

. 
. /*-----------------------
> TABLE D1:
> ITT estimates, Under 55 experiment,
> excluding subjects age 55+
> -----------------------*/
. 
. preserve

. keep if never_voted == 1
(394 observations deleted)

. 
. local treat_vars = " t3_1 t3_2 "

. 
. * define analysis sample condition
. local select = "under55==1 & flag_hh_mixedage!=1"

.                 
. * define ipw to use
. local ipw = "ipw_t3_hhmixed_nv"

.                 
. * construct state-by-cov interactions
. foreach st in GA LA MI NC TX {
  2. foreach v in age age2 d_race_black d_race_hisp d_race_other d_mar_married d_mar_unknown d_gend_f
> emale {
  3.         gen Z_`st'_`v' = d_st_`st' * `v'
  4.         quietly sum Z_`st'_`v' if `select'
  5.         if (r(sd) == . | r(sd) == 0) {
  6.                 drop Z_`st'_`v'
  7.                 }
  8.         }
  9. }

. 
. * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw, with cluster SE
. reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* [aweight=`ipw'] if `select',
>  vce(cluster hhid)
(sum of wgt is   8.3579e+05)

Linear regression                               Number of obs     =    278,462
                                                F(19, 268751)     =     209.47
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0274
                                                Root MSE          =     .33659

                              (Std. Err. adjusted for 268,752 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0098022    .002297     4.27   0.000     .0053002    .0143041
         t3_2 |   .0082795   .0023826     3.48   0.001     .0036097    .0129493
          age |  -.0033405   .0006626    -5.04   0.000    -.0046392   -.0020418
         age2 |   .0086336   .0010159     8.50   0.000     .0066426    .0106247
     age_miss |   .1645099   .0485308     3.39   0.001     .0693908    .2596289
      hhsize2 |   .0102338   .0042486     2.41   0.016     .0019067     .018561
      hhsize3 |   .0002159   .0210129     0.01   0.992    -.0409687    .0414005
      hhsize4 |  -.0690138   .0483211    -1.43   0.153    -.1637218    .0256941
 d_race_black |  -.0239882   .0023044   -10.41   0.000    -.0285048   -.0194716
  d_race_hisp |   -.049575   .0022483   -22.05   0.000    -.0539816   -.0451685
 d_race_other |   -.026891   .0035935    -7.48   0.000    -.0339341    -.019848
d_mar_married |   .0851218   .0036393    23.39   0.000     .0779889    .0922546
d_mar_unknown |   .1575161   .0524582     3.00   0.003     .0546995    .2603326
d_gend_female |   .0140386   .0016931     8.29   0.000     .0107201    .0173571
      d_st_GA |  -.0104776   .0040954    -2.56   0.011    -.0185045   -.0024506
      d_st_LA |    .067732   .0059117    11.46   0.000     .0561452    .0793188
      d_st_MI |  -.0770751   .0037796   -20.39   0.000     -.084483   -.0696672
      d_st_NC |  -.0010214   .0043138    -0.24   0.813    -.0094763    .0074335
      d_st_TX |   -.063699   .0034355   -18.54   0.000    -.0704326   -.0569654
        _cons |   .1885577   .0103836    18.16   0.000     .1682062    .2089092
-------------------------------------------------------------------------------

. local adjr2 = e(r2_a)

. qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)

. local c_turnout = r(mean)

. outreg2 using "TableD1_ITTEstimates_U55Exp_U55Subjects.xls", se bracket dec(3) label ctitle("Base S
> pecification") drop(Z*) ///
>         addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout", `c_turnout') addtext("
> State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Clustered SE?", Y) replace
TableD1_ITTEstimates_U55Exp_U55Subjects.xls
dir : seeout

. 
. * (2) all covs, YES state-by-cov interactions, with hhsize dummies, with ipw, with cluster SE   
. reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* Z_* [aweight=`ipw'] if `sele
> ct', vce(cluster hhid)
(sum of wgt is   8.3579e+05)

Linear regression                               Number of obs     =    278,462
                                                F(57, 268751)     =      80.06
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0309
                                                Root MSE          =     .33601

                                   (Std. Err. adjusted for 268,752 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |   .0097916   .0022915     4.27   0.000     .0053002    .0142829
              t3_2 |   .0082083   .0023771     3.45   0.001     .0035493    .0128674
               age |  -.0134196   .0024189    -5.55   0.000    -.0181605   -.0086786
              age2 |   .0228646   .0036922     6.19   0.000     .0156281    .0301011
          age_miss |   .1934273   .0493038     3.92   0.000     .0967932    .2900614
           hhsize2 |   .0103998   .0042274     2.46   0.014     .0021141    .0186855
           hhsize3 |   .0017442   .0209163     0.08   0.934    -.0392513    .0427396
           hhsize4 |  -.0635779   .0484817    -1.31   0.190    -.1586007    .0314449
      d_race_black |  -.0401917   .0073113    -5.50   0.000    -.0545216   -.0258618
       d_race_hisp |  -.0594077   .0113274    -5.24   0.000    -.0816091   -.0372062
      d_race_other |  -.0649662   .0145059    -4.48   0.000    -.0933973    -.036535
     d_mar_married |   .1051037   .0162929     6.45   0.000       .07317    .1370374
     d_mar_unknown |    .037035   .0872343     0.42   0.671    -.1339417    .2080118
     d_gend_female |   .0211744     .00638     3.32   0.001     .0086698    .0336791
           d_st_GA |  -.2922213    .045995    -6.35   0.000    -.3823703   -.2020723
           d_st_LA |  -.2390741   .0680279    -3.51   0.000     -.372407   -.1057412
           d_st_MI |    -.00204    .044885    -0.05   0.964    -.0900133    .0859333
           d_st_NC |  -.1340546   .0486353    -2.76   0.006    -.2293785   -.0387306
           d_st_TX |  -.2535275    .037637    -6.74   0.000     -.327295   -.1797601
          Z_GA_age |   .0168732   .0031011     5.44   0.000     .0107951    .0229513
         Z_GA_age2 |  -.0230021   .0047098    -4.88   0.000    -.0322331   -.0137711
 Z_GA_d_race_black |   .0216873   .0094777     2.29   0.022     .0031114    .0402633
  Z_GA_d_race_hisp |   .0217841   .0144932     1.50   0.133    -.0066221    .0501904
 Z_GA_d_race_other |   .0155937   .0176968     0.88   0.378    -.0190915     .050279
Z_GA_d_mar_married |   .0157743   .0195873     0.81   0.421    -.0226164     .054165
Z_GA_d_mar_unknown |   .1911961   .0859405     2.22   0.026     .0227551    .3596371
Z_GA_d_gend_female |   .0035678   .0082191     0.43   0.664    -.0125414     .019677
          Z_LA_age |   .0172388   .0044471     3.88   0.000     .0085226    .0259549
         Z_LA_age2 |  -.0229245    .006621    -3.46   0.001    -.0359015   -.0099476
 Z_LA_d_race_black |   .0297854   .0132454     2.25   0.025     .0038248    .0557461
  Z_LA_d_race_hisp |   .0073706   .0236179     0.31   0.755    -.0389198    .0536609
 Z_LA_d_race_other |   .0591609   .0283044     2.09   0.037      .003685    .1146368
Z_LA_d_mar_married |   .1182609   .0306729     3.86   0.000     .0581429    .1783789
Z_LA_d_mar_unknown |   .2269061   .0997286     2.28   0.023     .0314408    .4223715
Z_LA_d_gend_female |   .0065956   .0120291     0.55   0.583    -.0169812    .0301724
          Z_MI_age |  -.0051373   .0030286    -1.70   0.090    -.0110733    .0007987
         Z_MI_age2 |   .0061211   .0046287     1.32   0.186    -.0029511    .0151932
 Z_MI_d_race_black |   .0417871   .0093815     4.45   0.000     .0233996    .0601747
  Z_MI_d_race_hisp |   .0620409   .0149884     4.14   0.000      .032664    .0914178
 Z_MI_d_race_other |   .1123495   .0170717     6.58   0.000     .0788895    .1458096
Z_MI_d_mar_married |  -.0266558   .0187615    -1.42   0.155    -.0634279    .0101162
Z_MI_d_gend_female |   .0011863   .0074898     0.16   0.874    -.0134935    .0158662
          Z_NC_age |   .0071901   .0033763     2.13   0.033     .0005726    .0138075
         Z_NC_age2 |  -.0074094   .0052254    -1.42   0.156     -.017651    .0028323
 Z_NC_d_race_black |   .0273108   .0100277     2.72   0.006     .0076567    .0469649
  Z_NC_d_race_hisp |  -.0096545   .0141539    -0.68   0.495    -.0373957    .0180867
 Z_NC_d_race_other |   .0689217    .020474     3.37   0.001     .0287933    .1090501
Z_NC_d_mar_married |   .0020311   .0219168     0.09   0.926    -.0409253    .0449874
Z_NC_d_gend_female |  -.0118542    .008615    -1.38   0.169    -.0287393     .005031
          Z_TX_age |    .013463   .0025755     5.23   0.000     .0084151    .0185109
         Z_TX_age2 |   -.019488   .0039373    -4.95   0.000     -.027205   -.0117709
 Z_TX_d_race_black |   .0018244   .0080382     0.23   0.820    -.0139303    .0175791
  Z_TX_d_race_hisp |   .0021375   .0116399     0.18   0.854    -.0206763    .0249513
 Z_TX_d_race_other |   .0186359   .0152265     1.22   0.221    -.0112076    .0484793
Z_TX_d_mar_married |  -.0400061    .016932    -2.36   0.018    -.0731924   -.0068197
Z_TX_d_mar_unknown |  -.2192055    .082296    -2.66   0.008    -.3805035   -.0579076
Z_TX_d_gend_female |  -.0143372   .0067561    -2.12   0.034     -.027579   -.0010954
             _cons |   .3438291    .035495     9.69   0.000     .2742599    .4133983
------------------------------------------------------------------------------------

. local adjr2 = e(r2_a)

. qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)

. local c_turnout = r(mean)

. outreg2 using "TableD1_ITTEstimates_U55Exp_U55Subjects.xls", se bracket dec(3) label ctitle("With S
> tate-by-,Covariate Interactions") drop(Z*)  ///
>         addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout", `c_turnout') addtext("
> State-Covariate Interactions?", Y, "Weighted?", Y, "Household-Level Clustered SE?", Y) append
TableD1_ITTEstimates_U55Exp_U55Subjects.xls
dir : seeout

. 
. * (3) all covs, NO state-by-cov interactions, with hhsize dummies, WITHOUT ipw, WITHOUT cluster SE
. reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* if `select'

      Source |       SS           df       MS      Number of obs   =   278,462
-------------+----------------------------------   F(19, 278442)   =    421.11
       Model |  919.508196        19  48.3951682   Prob > F        =    0.0000
    Residual |   31999.489   278,442  .114923356   R-squared       =    0.0279
-------------+----------------------------------   Adj R-squared   =    0.0279
       Total |  32918.9972   278,461  .118217622   Root MSE        =      .339

-------------------------------------------------------------------------------
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0098151   .0022999     4.27   0.000     .0053073    .0143229
         t3_2 |   .0082826   .0023808     3.48   0.001     .0036164    .0129489
          age |  -.0033999   .0004661    -7.29   0.000    -.0043134   -.0024864
         age2 |   .0088343   .0007019    12.59   0.000     .0074585    .0102101
     age_miss |   .1495991   .0266707     5.61   0.000     .0973253    .2018728
      hhsize2 |   .0123004   .0026615     4.62   0.000     .0070839    .0175169
      hhsize3 |  -.0096605   .0113088    -0.85   0.393    -.0318253    .0125044
      hhsize4 |  -.0771403   .0399855    -1.93   0.054    -.1555108    .0012302
 d_race_black |  -.0255924   .0016978   -15.07   0.000    -.0289201   -.0222647
  d_race_hisp |  -.0487081   .0018246   -26.69   0.000    -.0522843   -.0451319
 d_race_other |  -.0215438   .0027068    -7.96   0.000     -.026849   -.0162387
d_mar_married |   .0848727   .0023429    36.23   0.000     .0802807    .0894646
d_mar_unknown |   .1911669    .028454     6.72   0.000     .1353978     .246936
d_gend_female |   .0145751   .0013425    10.86   0.000     .0119438    .0172064
      d_st_GA |  -.0089635   .0028216    -3.18   0.001    -.0144938   -.0034331
      d_st_LA |   .0713803   .0037339    19.12   0.000      .064062    .0786987
      d_st_MI |  -.0772309   .0027605   -27.98   0.000    -.0826413   -.0718204
      d_st_NC |  -.0050204   .0029077    -1.73   0.084    -.0107195    .0006787
      d_st_TX |  -.0658236   .0023977   -27.45   0.000    -.0705229   -.0611243
        _cons |   .1889992   .0074455    25.38   0.000     .1744061    .2035922
-------------------------------------------------------------------------------

. local adjr2 = e(r2_a)

. qui sum voted14 if t2==0 & e(sample)

. local c_turnout = r(mean)

. outreg2 using "TableD1_ITTEstimates_U55Exp_U55Subjects.xls", se bracket dec(3) label ctitle("Unweig
> hted and,Without HH-Level,Clustered SE") drop(Z*)  ///
>         addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout", `c_turnout') addtext("
> State-Covariate Interactions?", N, "Weighted?", N, "Household-Level Clustered SE?", N) append
TableD1_ITTEstimates_U55Exp_U55Subjects.xls
dir : seeout

. 
. * drop interactions
. drop Z_*

. 
. restore

. 
. /*-----------------------
> TABLE D2:
> ITT estimates by HH size
> -----------------------*/
. 
. preserve

. 
. local treat_vars = " t3_1 t3_2 "

. 
.         * loop over under/over 55 subgroups
.         forvalues u = 1(-1)0 {
  2.         
.         if (`u' == 1) {                 // UNDER 55 ANALYSIS
  3.                 foreach h in 1 2 {      // SET HOUSEHOLD SIZE (1 OR 2)
  4.                 
.                 * define analysis sample condition
.                 local select = "under55==`u' & hhsize == `h' & never_voted == 1 & flag_hh_mixed_nv 
> != 1"
  5.                 
.                 * define ipw to use
.                 local ipw = "ipw_t3_hh_nv"
  6.                 
.                 * construct state-by-cov interactions
.                 foreach st in GA LA MI NC TX {
  7.                 foreach v in age age2 d_race_black d_race_hisp d_race_other d_mar_married d_mar_
> unknown d_gend_female {
  8.                         gen Z_`st'_`v' = d_st_`st' * `v'
  9.                         quietly sum Z_`st'_`v' if `select'
 10.                         if (r(sd) == . | r(sd) == 0) {
 11.                                 drop Z_`st'_`v'
 12.                                 }
 13.                         }
 14.                 }
 15.                 
.                 * estimate and save results
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         if (`h' == 1) {
 16.                         reg voted14 `treat_vars' age age2 age_miss d_* [aweight=`ipw'] if `selec
> t', vce(cluster hhid)
 17.                         local adjr2 = e(r2_a)
 18.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 19.                         local c_turnout = r(mean)
 20.                         outreg2 using "TableD2_ITTEstimatesByHHSize.xls", se bracket dec(3) labe
> l ctitle("Under 55 Exp,HH Size=`h',Base Specification") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) replace
 21.                         }
 22.                         else {
 23.                         reg voted14 `treat_vars' age age2 age_miss d_* [aweight=`ipw'] if `selec
> t', vce(cluster hhid)
 24.                         local adjr2 = e(r2_a)
 25.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 26.                         local c_turnout = r(mean)
 27.                         outreg2 using "TableD2_ITTEstimatesByHHSize.xls", se bracket dec(3) labe
> l ctitle("Under 55 Exp,HH Size=`h',Base Specification") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 28. 
.                         }
 29.                         
.                         * (2) all covs, YES state-by-cov interactions, with hhsize dummies, with ip
> w, with cluster SE   
.                         reg voted14 `treat_vars' age age2 age_miss d_* Z_* [aweight=`ipw'] if `sele
> ct', vce(cluster hhid)
 30.                         local adjr2 = e(r2_a)
 31.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 32.                         local c_turnout = r(mean)
 33.                         outreg2 using "TableD2_ITTEstimatesByHHSize.xls", se bracket dec(3) labe
> l ctitle("Under 55 Exp,HH Size=`h',With State-by-,Covariate,Interactions") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", Y, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 34.                         
. 
.                         * drop interactions
.                         drop Z_*
 35.                 
.                 }
 36.         }
 37.         else {                                  // OVER 55 ANALYSIS
 38.         local h = 1                             // SET HOUSEHOLD SIZE (1 ONLY)
 39.                 * define analysis sample condition
.                 local select = "under55==`u' & hhsize == `h' & never_voted == 1 & flag_hh_mixed_nv 
> != 1"
 40.                 
.                 * define ipw to use
.                 local ipw = "ipw_t3_hh_fs"
 41.                 
.                 * construct state-by-cov interactions
.                 foreach st in GA LA MI NC TX {
 42.                 foreach v in age age2 d_race_black d_race_hisp d_race_other d_mar_married d_mar_
> unknown d_gend_female {
 43.                         gen Z_`st'_`v' = d_st_`st' * `v'
 44.                         quietly sum Z_`st'_`v' if `select'
 45.                         if (r(sd) == . | r(sd) == 0) {
 46.                                 drop Z_`st'_`v'
 47.                                 }
 48.                         }
 49.                 }
 50.                 
.                 * estimate and save results
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss d_* [aweight=`ipw'] if `select',
>  vce(cluster hhid)
 51.                         local adjr2 = e(r2_a)
 52.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 53.                         local c_turnout = r(mean)
 54.                         outreg2 using "TableD2_ITTEstimatesByHHSize.xls", se bracket dec(3) labe
> l ctitle("Over 55 Exp,HH Size=`h',Base Specification") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 55. 
.                         * (2) all covs, YES state-by-cov interactions, with hhsize dummies, with ip
> w, with cluster SE   
.                         reg voted14 `treat_vars' age age2 age_miss d_* Z_* [aweight=`ipw'] if `sele
> ct', vce(cluster hhid)
 56.                         local adjr2 = e(r2_a)
 57.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 58.                         local c_turnout = r(mean)
 59.                         outreg2 using "TableD2_ITTEstimatesByHHSize.xls", se bracket dec(3) labe
> l ctitle("Over 55 Exp,HH Size=`h',With State-by-,Covariate,Interactions") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", Y, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 60.                         
. 
.                         * drop interactions
.                         drop Z_*
 61.                                 
.         }
 62.         
.         }
(sum of wgt is   7.7811e+05)

Linear regression                               Number of obs     =    259,369
                                                F(16, 259368)     =     223.34
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0256
                                                Root MSE          =     .33529

                              (Std. Err. adjusted for 259,369 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0093987   .0023301     4.03   0.000     .0048317    .0139657
         t3_2 |   .0068286   .0024134     2.83   0.005     .0020983    .0115589
          age |  -.0035365   .0006565    -5.39   0.000    -.0048233   -.0022497
         age2 |   .0086816   .0010038     8.65   0.000     .0067141    .0106491
     age_miss |   .1713956   .0487548     3.52   0.000     .0758376    .2669537
 d_race_black |  -.0233923   .0023478    -9.96   0.000    -.0279939   -.0187908
  d_race_hisp |  -.0484149   .0022824   -21.21   0.000    -.0528885   -.0439414
 d_race_other |  -.0328055   .0035996    -9.11   0.000    -.0398606   -.0257503
d_mar_married |   .0817726   .0038156    21.43   0.000     .0742942     .089251
d_mar_unknown |   .1650303   .0525787     3.14   0.002     .0619775    .2680831
d_gend_female |   .0145575   .0017738     8.21   0.000     .0110809    .0180341
      d_st_GA |  -.0132169   .0041675    -3.17   0.002    -.0213852   -.0050487
      d_st_LA |   .0642322     .00601    10.69   0.000     .0524528    .0760116
      d_st_MI |  -.0778048   .0038708   -20.10   0.000    -.0853914   -.0702183
      d_st_NC |  -.0043863   .0043823    -1.00   0.317    -.0129754    .0042029
      d_st_TX |  -.0652345    .003511   -18.58   0.000    -.0721159    -.058353
        _cons |   .1957608   .0103666    18.88   0.000     .1754425    .2160791
-------------------------------------------------------------------------------
TableD2_ITTEstimatesByHHSize.xls
dir : seeout
(sum of wgt is   7.7811e+05)

Linear regression                               Number of obs     =    259,369
                                                F(54, 259368)     =      75.84
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0289
                                                Root MSE          =     .33476

                                   (Std. Err. adjusted for 259,369 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |   .0093845   .0023254     4.04   0.000     .0048268    .0139423
              t3_2 |   .0067755   .0024085     2.81   0.005     .0020549    .0114961
               age |  -.0137676   .0024913    -5.53   0.000    -.0186504   -.0088848
              age2 |   .0231043    .003808     6.07   0.000     .0156407    .0305679
          age_miss |   .1938007   .0495901     3.91   0.000     .0966055     .290996
      d_race_black |  -.0372968     .00757    -4.93   0.000    -.0521338   -.0224597
       d_race_hisp |   -.063757   .0112207    -5.68   0.000    -.0857494   -.0417647
      d_race_other |  -.0684119   .0149891    -4.56   0.000    -.0977902   -.0390336
     d_mar_married |   .1194401   .0173625     6.88   0.000     .0854101    .1534701
     d_mar_unknown |   .0779814   .0871276     0.90   0.371    -.0927863     .248749
     d_gend_female |   .0202773   .0066381     3.05   0.002     .0072668    .0332878
           d_st_GA |  -.2865991   .0472226    -6.07   0.000    -.3791541   -.1940441
           d_st_LA |  -.2447065   .0697744    -3.51   0.000    -.3814625   -.1079505
           d_st_MI |  -.0089267   .0458944    -0.19   0.846    -.0988785    .0810251
           d_st_NC |  -.1294621   .0499553    -2.59   0.010    -.2273731   -.0315512
           d_st_TX |  -.2617253     .03844    -6.81   0.000    -.3370666   -.1863841
          Z_GA_age |   .0162887   .0031834     5.12   0.000     .0100493    .0225281
         Z_GA_age2 |  -.0220908     .00484    -4.56   0.000    -.0315771   -.0126045
 Z_GA_d_race_black |     .02175   .0097304     2.24   0.025     .0026788    .0408213
  Z_GA_d_race_hisp |   .0292498    .014395     2.03   0.042     .0010359    .0574636
 Z_GA_d_race_other |   .0139357   .0181064     0.77   0.442    -.0215524    .0494239
Z_GA_d_mar_married |  -.0028546   .0207506    -0.14   0.891    -.0435252    .0378161
Z_GA_d_mar_unknown |   .1477202   .0860623     1.72   0.086    -.0209596       .3164
Z_GA_d_gend_female |   .0051195   .0085561     0.60   0.550    -.0116502    .0218891
          Z_LA_age |   .0175377   .0045611     3.85   0.000     .0085981    .0264773
         Z_LA_age2 |  -.0232551   .0067962    -3.42   0.001    -.0365754   -.0099348
 Z_LA_d_race_black |   .0261028   .0135482     1.93   0.054    -.0004513    .0526569
  Z_LA_d_race_hisp |   .0092383   .0238443     0.39   0.698    -.0374958    .0559724
 Z_LA_d_race_other |   .0707705   .0290272     2.44   0.015     .0138778    .1276631
Z_LA_d_mar_married |   .0904058   .0321743     2.81   0.005     .0273452    .1534665
Z_LA_d_mar_unknown |   .1846191   .0995478     1.85   0.064    -.0104918    .3797301
Z_LA_d_gend_female |   .0078518   .0124839     0.63   0.529    -.0166164    .0323199
          Z_MI_age |  -.0045066   .0030924    -1.46   0.145    -.0105676    .0015545
         Z_MI_age2 |   .0049375    .004724     1.05   0.296    -.0043214    .0141964
 Z_MI_d_race_black |   .0350882   .0095987     3.66   0.000      .016275    .0539014
  Z_MI_d_race_hisp |   .0718943    .015366     4.68   0.000     .0417773    .1020113
 Z_MI_d_race_other |   .1036454   .0175644     5.90   0.000     .0692197    .1380711
Z_MI_d_mar_married |  -.0525504   .0195792    -2.68   0.007     -.090925   -.0141757
Z_MI_d_gend_female |   .0041434   .0078138     0.53   0.596    -.0111715    .0194583
          Z_NC_age |   .0066095   .0034726     1.90   0.057    -.0001967    .0134157
         Z_NC_age2 |  -.0063947   .0053885    -1.19   0.235     -.016956    .0041665
 Z_NC_d_race_black |   .0241092   .0102506     2.35   0.019     .0040183    .0442001
  Z_NC_d_race_hisp |  -.0008362   .0142137    -0.06   0.953    -.0286948    .0270223
 Z_NC_d_race_other |   .0558628   .0206005     2.71   0.007     .0154864    .0962391
Z_NC_d_mar_married |  -.0178119   .0234943    -0.76   0.448    -.0638601    .0282362
Z_NC_d_gend_female |   -.008428    .008901    -0.95   0.344    -.0258737    .0090176
          Z_TX_age |   .0139006   .0026262     5.29   0.000     .0087534    .0190479
         Z_TX_age2 |   -.020122   .0040162    -5.01   0.000    -.0279936   -.0122504
 Z_TX_d_race_black |   .0001242   .0083036     0.01   0.988    -.0161507    .0163991
  Z_TX_d_race_hisp |   .0078498   .0115449     0.68   0.497    -.0147779    .0304775
 Z_TX_d_race_other |   .0182355    .015677     1.16   0.245     -.012491    .0489619
Z_TX_d_mar_married |  -.0568303   .0180116    -3.16   0.002    -.0921325    -.021528
Z_TX_d_mar_unknown |  -.2508509   .0830946    -3.02   0.003    -.4137141   -.0879878
Z_TX_d_gend_female |  -.0134535   .0070405    -1.91   0.056    -.0272526    .0003456
             _cons |   .3529516   .0365704     9.65   0.000     .2812746    .4246286
------------------------------------------------------------------------------------
TableD2_ITTEstimatesByHHSize.xls
dir : seeout
(sum of wgt is   6.2466e+04)

Linear regression                               Number of obs     =     20,822
                                                F(15, 10410)      =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0545
                                                Root MSE          =     .35693

                               (Std. Err. adjusted for 10,411 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0172358   .0104576     1.65   0.099    -.0032631    .0377346
         t3_2 |   .0263306   .0108999     2.42   0.016     .0049646    .0476965
          age |   .0076124   .0015024     5.07   0.000     .0046674    .0105574
         age2 |  -.0050717   .0019474    -2.60   0.009     -.008889   -.0012545
     age_miss |  -.1651356   .0168054    -9.83   0.000    -.1980774   -.1321938
 d_race_black |   -.023802    .010577    -2.25   0.024     -.044535    -.003069
  d_race_hisp |  -.0429116   .0104628    -4.10   0.000    -.0634207   -.0224024
 d_race_other |  -.0003117    .012972    -0.02   0.981    -.0257393    .0251159
d_mar_married |   .0831599   .0103929     8.00   0.000     .0627878    .1035319
d_mar_unknown |   .2038623   .1165329     1.75   0.080    -.0245645    .4322892
d_gend_female |   .0081748   .0053915     1.52   0.129    -.0023936    .0187432
      d_st_GA |   .0276987   .0190163     1.46   0.145    -.0095769    .0649742
      d_st_LA |   .1284099   .0292563     4.39   0.000      .071062    .1857578
      d_st_MI |  -.0660309   .0162407    -4.07   0.000    -.0978659    -.034196
      d_st_NC |    .040617   .0201788     2.01   0.044     .0010626    .0801714
      d_st_TX |  -.0557284   .0152817    -3.65   0.000    -.0856834   -.0257734
        _cons |  -.0182836   .0287566    -0.64   0.525    -.0746521    .0380849
-------------------------------------------------------------------------------
TableD2_ITTEstimatesByHHSize.xls
dir : seeout
(sum of wgt is   6.2466e+04)

Linear regression                               Number of obs     =     20,822
                                                F(51, 10410)      =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0677
                                                Root MSE          =     .35475

                                    (Std. Err. adjusted for 10,411 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |   .0177518   .0103206     1.72   0.085    -.0024785    .0379822
              t3_2 |   .0263348   .0107665     2.45   0.014     .0052303    .0474392
               age |    .003192   .0055868     0.57   0.568    -.0077592    .0141432
              age2 |   .0004425   .0070882     0.06   0.950    -.0134518    .0143368
          age_miss |  -.1841963   .0413256    -4.46   0.000    -.2652023   -.1031902
      d_race_black |   -.063771   .0274735    -2.32   0.020    -.1176244   -.0099177
       d_race_hisp |    .041604   .0554237     0.75   0.453    -.0670372    .1502451
      d_race_other |   .0572713   .0757838     0.76   0.450    -.0912795    .2058221
     d_mar_married |   .0062528   .0424618     0.15   0.883    -.0769805    .0894861
     d_mar_unknown |  -.0327099   .0709221    -0.46   0.645    -.1717307     .106311
     d_gend_female |   .0275912   .0233996     1.18   0.238    -.0182766    .0734589
           d_st_GA |   -.265408   .1169121    -2.27   0.023    -.4945782   -.0362378
           d_st_LA |  -.2457954   .1828929    -1.34   0.179    -.6043006    .1127098
           d_st_MI |  -.1559535   .1156685    -1.35   0.178     -.382686    .0707791
           d_st_NC |  -.0621574   .1276826    -0.49   0.626    -.3124398     .188125
           d_st_TX |  -.0726106   .0942885    -0.77   0.441    -.2574343     .112213
          Z_GA_age |   .0162295   .0071122     2.28   0.023     .0022883    .0301708
         Z_GA_age2 |  -.0183336   .0090812    -2.02   0.044    -.0361346   -.0005327
 Z_GA_d_race_black |   .0058522   .0420838     0.14   0.889    -.0766402    .0883445
  Z_GA_d_race_hisp |  -.0753781   .0731641    -1.03   0.303    -.2187937    .0680375
 Z_GA_d_race_other |  -.1134488   .0884456    -1.28   0.200    -.2868191    .0599215
Z_GA_d_mar_married |   .0980492   .0533544     1.84   0.066    -.0065356     .202634
Z_GA_d_mar_unknown |   .7940485   .1768679     4.49   0.000     .4473535    1.140743
Z_GA_d_gend_female |  -.0089721    .029236    -0.31   0.759    -.0662802     .048336
          Z_LA_age |   .0148347   .0107646     1.38   0.168    -.0062659    .0359354
         Z_LA_age2 |  -.0162189   .0131183    -1.24   0.216    -.0419333    .0094955
 Z_LA_d_race_black |   .0698715   .0676191     1.03   0.301    -.0626749     .202418
  Z_LA_d_race_hisp |   .0263277   .1229416     0.21   0.830    -.2146614    .2673169
 Z_LA_d_race_other |  -.1322097    .126846    -1.04   0.297    -.3808521    .1164328
Z_LA_d_mar_married |   .2550995   .0805703     3.17   0.002     .0971663    .4130328
Z_LA_d_gend_female |   .0208084   .0421122     0.49   0.621    -.0617396    .1033565
          Z_MI_age |   .0027422   .0071547     0.38   0.702    -.0112823    .0167668
         Z_MI_age2 |  -.0028274   .0092416    -0.31   0.760    -.0209427    .0152878
 Z_MI_d_race_black |   .1174518    .037401     3.14   0.002     .0441386    .1907651
  Z_MI_d_race_hisp |  -.0729183    .060748    -1.20   0.230    -.1919961    .0461595
 Z_MI_d_race_other |    .077018     .08124     0.95   0.343     -.082228     .236264
Z_MI_d_mar_married |   .1353439   .0533309     2.54   0.011     .0308051    .2398827
Z_MI_d_gend_female |  -.0340234   .0261963    -1.30   0.194    -.0853732    .0173263
          Z_NC_age |   .0038223   .0077728     0.49   0.623     -.011414    .0190586
         Z_NC_age2 |  -.0018606   .0098976    -0.19   0.851    -.0212618    .0175406
 Z_NC_d_race_black |   .0769838   .0457012     1.68   0.092    -.0125994     .166567
  Z_NC_d_race_hisp |  -.1119056   .0673145    -1.66   0.096    -.2438549    .0200437
 Z_NC_d_race_other |  -.0059016   .0883232    -0.07   0.947    -.1790321    .1672288
Z_NC_d_mar_married |    .098241   .0561959     1.75   0.080    -.0119138    .2083959
Z_NC_d_gend_female |  -.0454597   .0332124    -1.37   0.171    -.1105623    .0196429
          Z_TX_age |   .0037325   .0059036     0.63   0.527    -.0078397    .0153046
         Z_TX_age2 |  -.0054694   .0075144    -0.73   0.467     -.020199    .0092602
 Z_TX_d_race_black |   .0091635   .0314863     0.29   0.771    -.0525556    .0708826
  Z_TX_d_race_hisp |   -.114206     .05696    -2.01   0.045    -.2258584   -.0025535
 Z_TX_d_race_other |  -.1047581   .0777195    -1.35   0.178    -.2571032    .0475871
Z_TX_d_mar_married |    .054337   .0442802     1.23   0.220    -.0324607    .1411348
Z_TX_d_mar_unknown |    .146234   .1054991     1.39   0.166    -.0605644    .3530324
Z_TX_d_gend_female |  -.0199808     .02433    -0.82   0.412    -.0676722    .0277107
             _cons |   .0556448   .0893424     0.62   0.533    -.1194835    .2307731
------------------------------------------------------------------------------------
TableD2_ITTEstimatesByHHSize.xls
dir : seeout
(sum of wgt is   6.2376e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     31,184
                                                F(13, 31183)      =      35.86
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0409
                                                Root MSE          =     .42301

                               (Std. Err. adjusted for 31,184 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0002876   .0079796     0.04   0.971    -.0153527    .0159279
         t3_2 |          0  (omitted)
          age |   .0398816   .0077606     5.14   0.000     .0246706    .0550925
         age2 |  -.0275429   .0057034    -4.83   0.000    -.0387217   -.0163641
     age_miss |          0  (omitted)
 d_race_black |  -.0310125   .0117947    -2.63   0.009    -.0541307   -.0078944
  d_race_hisp |  -.0550771   .0125554    -4.39   0.000    -.0796862    -.030468
 d_race_other |  -.0994811   .0143933    -6.91   0.000    -.1276924   -.0712697
d_mar_married |   .1098232   .0134202     8.18   0.000     .0835192    .1361273
d_mar_unknown |          0  (omitted)
d_gend_female |   .0363918    .009486     3.84   0.000     .0177988    .0549848
      d_st_GA |  -.0313391   .0187127    -1.67   0.094    -.0680168    .0053385
      d_st_LA |    .146604   .0255704     5.73   0.000     .0964849    .1967231
      d_st_MI |  -.1011124    .019448    -5.20   0.000    -.1392313   -.0629935
      d_st_NC |   .0528114   .0211338     2.50   0.012     .0113883    .0942345
      d_st_TX |  -.0889762      .0168    -5.30   0.000    -.1219047   -.0560476
        _cons |  -1.115629   .2615584    -4.27   0.000    -1.628294   -.6029638
-------------------------------------------------------------------------------
TableD2_ITTEstimatesByHHSize.xls
dir : seeout
(sum of wgt is   6.2376e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     31,184
                                                F(48, 31183)      =      12.58
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0487
                                                Root MSE          =     .42152

                                    (Std. Err. adjusted for 31,184 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |   .0010457   .0079358     0.13   0.895    -.0145088    .0166003
              t3_2 |          0  (omitted)
               age |   .0294479   .0336019     0.88   0.381    -.0364132     .095309
              age2 |  -.0207294   .0250816    -0.83   0.409    -.0698903    .0284314
          age_miss |          0  (omitted)
      d_race_black |  -.0679533   .0403812    -1.68   0.092     -.147102    .0111953
       d_race_hisp |  -.1570982    .061644    -2.55   0.011    -.2779228   -.0362736
      d_race_other |  -.2113245   .0600289    -3.52   0.000    -.3289835   -.0936655
     d_mar_married |   .1434865   .0566696     2.53   0.011     .0324119    .2545612
     d_mar_unknown |          0  (omitted)
     d_gend_female |  -.0180946   .0392569    -0.46   0.645    -.0950397    .0588504
           d_st_GA |  -.1382612   1.290041    -0.11   0.915    -2.666794    2.390271
           d_st_LA |  -1.188174    1.89285    -0.63   0.530    -4.898236    2.521888
           d_st_MI |  -1.346548   1.311378    -1.03   0.305    -3.916902    1.223805
           d_st_NC |  -1.218222   1.385581    -0.88   0.379    -3.934017    1.497573
           d_st_TX |   -.227363   1.168715    -0.19   0.846    -2.518091    2.063365
          Z_GA_age |   .0013124   .0386579     0.03   0.973    -.0744587    .0770835
         Z_GA_age2 |  -.0013942   .0286611    -0.05   0.961    -.0575712    .0547828
 Z_GA_d_race_black |   .0258186   .0504504     0.51   0.609    -.0730662    .1247035
  Z_GA_d_race_hisp |   .1197041   .0746853     1.60   0.109    -.0266821    .2660903
 Z_GA_d_race_other |   .1017054   .0722465     1.41   0.159    -.0399006    .2433115
Z_GA_d_mar_married |  -.0226281   .0660714    -0.34   0.732    -.1521306    .1068744
Z_GA_d_gend_female |   .0939083   .0455736     2.06   0.039     .0045823    .1832344
          Z_LA_age |   .0301407   .0574066     0.53   0.600    -.0823786    .1426601
         Z_LA_age2 |  -.0206128   .0431335    -0.48   0.633    -.1051562    .0639306
 Z_LA_d_race_black |   .2309939   .0649609     3.56   0.000     .1036678    .3583199
  Z_LA_d_race_hisp |   .4834584    .104113     4.64   0.000     .2793928     .687524
 Z_LA_d_race_other |   .4180317   .1151915     3.63   0.000     .1922519    .6438116
Z_LA_d_mar_married |   .0515221   .0903734     0.57   0.569    -.1256135    .2286576
Z_LA_d_gend_female |   .1156568   .0610037     1.90   0.058    -.0039129    .2352265
          Z_MI_age |   .0345224    .039449     0.88   0.382    -.0427992    .1118441
         Z_MI_age2 |  -.0241718   .0292773    -0.83   0.409    -.0815565     .033213
 Z_MI_d_race_black |   .0062449     .05199     0.12   0.904    -.0956576    .1081474
  Z_MI_d_race_hisp |   .2103634   .0846758     2.48   0.013     .0443954    .3763313
 Z_MI_d_race_other |   .1513619   .0714014     2.12   0.034     .0114122    .2913116
Z_MI_d_mar_married |  -.0762634     .07984    -0.96   0.339    -.2327531    .0802263
Z_MI_d_gend_female |   .0246473   .0522642     0.47   0.637    -.0777925    .1270872
          Z_NC_age |   .0342247   .0414263     0.83   0.409    -.0469726    .1154219
         Z_NC_age2 |  -.0249901   .0306199    -0.82   0.414    -.0850064    .0350262
 Z_NC_d_race_black |    .131183   .0561464     2.34   0.019     .0211337    .2412322
  Z_NC_d_race_hisp |   .0627575   .0794416     0.79   0.430    -.0929512    .2184661
 Z_NC_d_race_other |   .1037249   .0776926     1.34   0.182    -.0485556    .2560055
Z_NC_d_mar_married |   .0632467   .0786786     0.80   0.421    -.0909664    .2174598
Z_NC_d_gend_female |   .0798579   .0553781     1.44   0.149    -.0286854    .1884013
          Z_TX_age |   .0016028   .0352376     0.05   0.964    -.0674643    .0706698
         Z_TX_age2 |   .0001038   .0262733     0.00   0.997    -.0513928    .0516004
 Z_TX_d_race_black |  -.0064461   .0438224    -0.15   0.883    -.0923397    .0794475
  Z_TX_d_race_hisp |   .0754288     .06353     1.19   0.235    -.0490925    .1999502
 Z_TX_d_race_other |   .0830644   .0628755     1.32   0.186    -.0401742    .2063029
Z_TX_d_mar_married |  -.0525585   .0589483    -0.89   0.373    -.1680994    .0629825
Z_TX_d_gend_female |    .045914   .0409947     1.12   0.263    -.0344373    .1262652
             _cons |   -.669149   1.113302    -0.60   0.548    -2.851266    1.512968
------------------------------------------------------------------------------------
TableD2_ITTEstimatesByHHSize.xls
dir : seeout

.         
. 
. 
. restore

. 
. /*-----------------------
> TABLE D3: 
> ITT estimates by age category
> among subjects in 1-person HH
> -----------------------*/
. 
. preserve

. keep if never_voted == 1
(394 observations deleted)

. local treat_vars = " t3_1 t3_2 "

. 
.         forvalues u = 1(-1)0 {
  2.         
.         foreach a in 17 25 35 45 55 65 75 85 {
  3.         
.                 * define analysis sample condition
.                 local select = "under55==`u' & hhsize==1 & agecat==`a'"
  4.                 di "`select'"
  5. 
.                 * define ipw to use
.                 local ipw = "ipw_t3_hh1_age_nv"
  6.         
.                 if `a' == 17 {
  7.                         local agegrp = "17-24"
  8.                 }
  9.                 else if `a' == 25 {
 10.                         local agegrp = "25-34"
 11.                 }
 12.                 else if `a' == 35 {
 13.                         local agegrp = "35-44"
 14.                 }
 15.                 else if `a' == 45 {
 16.                         local agegrp = "45-54"
 17.                 }
 18.                 else if `a' == 55 {
 19.                         local agegrp = "55-64"
 20.                 }
 21.                 else if `a' == 65 {
 22.                         local agegrp = "65-74"
 23.                 }
 24.                 else if `a' == 75 {
 25.                         local agegrp = "75-84"
 26.                 }
 27.                 else if `a' == 85 {
 28.                         local agegrp = "85-90"
 29.                 }
 30.         
.         
.                 if (`u' == 1 & (`a' == 17 | `a' == 25 | `a' == 35 | `a' == 45)) {                  
>      // UNDER 55 ANALYSIS
 31.                                 
.                         if (`a' == 17) {
 32.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 d_* [aweight=`ipw'] if `select', vce(clus
> ter hhid)
 33.                         local adjr2 = e(r2_a)
 34.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 35.                         local c_turnout = r(mean)
 36.                         outreg2 using "TableD3_ITTEstimatesByAgeCat_HH1Only.xls", se bracket dec
> (3) label ctitle("Under 55,Experiment,`agegrp'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) replace
 37.                         }
 38.                         else {
 39.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 d_* [aweight=`ipw'] if `select', vce(clus
> ter hhid)
 40.                         local adjr2 = e(r2_a)
 41.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 42.                         local c_turnout = r(mean)
 43.                         outreg2 using "TableD3_ITTEstimatesByAgeCat_HH1Only.xls", se bracket dec
> (3) label ctitle("Under 55,Experiment,`agegrp'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 44.                         }
 45.                         
. 
.                 }
 46.                 else if (`u' == 0 & (`a' == 55 | `a' == 65 | `a' == 75 | `a' == 85)) {          
>                         // OVER 55 ANALYSIS
 47.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' age age2 d_* [aweight=`ipw'] if `select', vce(clus
> ter hhid)
 48.                         local adjr2 = e(r2_a)
 49.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 50.                         local c_turnout = r(mean)
 51.                         outreg2 using "TableD3_ITTEstimatesByAgeCat_HH1Only.xls", se bracket dec
> (3) label ctitle("Over 55,Experiment,`agegrp'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 52.                                         
.                 }
 53.                 else {
 54.                         di "No analysis for this combination"
 55. 
.                 }
 56.                 
.                 
.                 
.                 }
 57.                 
.         }
under55==1 & hhsize==1 & agecat==17
(sum of wgt is   4.0352e+05)

Linear regression                               Number of obs     =    134,508
                                                F(15, 134507)     =     117.05
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0211
                                                Root MSE          =     .31732

                              (Std. Err. adjusted for 134,508 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0065958    .003046     2.17   0.030     .0006258    .0125658
         t3_2 |   .0067932   .0031625     2.15   0.032     .0005947    .0129917
          age |  -.2279164   .0149587   -15.24   0.000    -.2572352   -.1985975
         age2 |   .5209152   .0357665    14.56   0.000     .4508136    .5910168
 d_race_black |  -.0176694   .0030322    -5.83   0.000    -.0236124   -.0117263
  d_race_hisp |  -.0461336   .0028193   -16.36   0.000    -.0516594   -.0406079
 d_race_other |  -.0353675   .0057763    -6.12   0.000     -.046689   -.0240459
d_mar_married |    .011933   .0065967     1.81   0.070    -.0009964    .0248623
d_mar_unknown |   .1995963   .0843347     2.37   0.018      .034302    .3648907
d_gend_female |   .0108794   .0022922     4.75   0.000     .0063867     .015372
      d_st_GA |  -.0221327   .0053506    -4.14   0.000    -.0326198   -.0116457
      d_st_LA |   .0478175   .0082058     5.83   0.000     .0317342    .0639008
      d_st_MI |  -.0503004   .0050507    -9.96   0.000    -.0601997   -.0404011
      d_st_NC |  -.0247754   .0053957    -4.59   0.000    -.0353508      -.0142
      d_st_TX |  -.0698408   .0044762   -15.60   0.000    -.0786142   -.0610675
        _cons |   2.619407   .1552631    16.87   0.000     2.315094    2.923719
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & agecat==25
(sum of wgt is   2.0381e+05)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     67,938
                                                F(14, 67937)      =      76.16
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0281
                                                Root MSE          =     .33379

                               (Std. Err. adjusted for 67,938 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0131204   .0045109     2.91   0.004      .004279    .0219618
         t3_2 |   .0056773   .0046617     1.22   0.223    -.0034597    .0148143
          age |   .0442292   .0132283     3.34   0.001     .0183019    .0701566
         age2 |  -.0716914   .0226095    -3.17   0.002    -.1160061   -.0273767
 d_race_black |  -.0351009   .0045908    -7.65   0.000    -.0440989   -.0261028
  d_race_hisp |  -.0568525   .0045566   -12.48   0.000    -.0657834   -.0479216
 d_race_other |  -.0508462   .0060427    -8.41   0.000    -.0626899   -.0390025
d_mar_married |   .0894954    .006378    14.03   0.000     .0769945    .1019962
d_mar_unknown |          0  (omitted)
d_gend_female |   .0170076   .0035013     4.86   0.000      .010145    .0238702
      d_st_GA |   .0054004    .008343     0.65   0.517    -.0109518    .0217526
      d_st_LA |   .0913865    .011347     8.05   0.000     .0691464    .1136267
      d_st_MI |  -.0845545   .0073876   -11.45   0.000    -.0990343   -.0700748
      d_st_NC |   .0051847   .0093582     0.55   0.580    -.0131574    .0235268
      d_st_TX |  -.0486027   .0070618    -6.88   0.000    -.0624438   -.0347615
        _cons |  -.5130807   .1918462    -2.67   0.007    -.8890991   -.1370624
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & agecat==35
(sum of wgt is   1.0215e+05)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     34,051
                                                F(14, 34050)      =      37.53
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0299
                                                Root MSE          =     .36382

                               (Std. Err. adjusted for 34,051 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .002745   .0071667     0.38   0.702     -.011302     .016792
         t3_2 |  -.0000261   .0073893    -0.00   0.997    -.0145095    .0144572
          age |   .0565278   .0277638     2.04   0.042     .0021098    .1109458
         age2 |  -.0694635   .0353131    -1.97   0.049    -.1386783   -.0002487
 d_race_black |  -.0196628   .0082132    -2.39   0.017    -.0357609   -.0035647
  d_race_hisp |  -.0360399   .0083153    -4.33   0.000    -.0523381   -.0197416
 d_race_other |  -.0137228   .0094936    -1.45   0.148    -.0323306     .004885
d_mar_married |    .100224   .0082764    12.11   0.000      .084002    .1164459
d_mar_unknown |          0  (omitted)
d_gend_female |   .0233655   .0059476     3.93   0.000     .0117079     .035023
      d_st_GA |   .0195222   .0135538     1.44   0.150    -.0070437    .0460881
      d_st_LA |   .0965609   .0185277     5.21   0.000     .0602459    .1328758
      d_st_MI |  -.0889346   .0134122    -6.63   0.000    -.1152229   -.0626463
      d_st_NC |   .0269206   .0157671     1.71   0.088    -.0039836    .0578247
      d_st_TX |  -.0700042   .0118295    -5.92   0.000    -.0931903   -.0468181
        _cons |  -.9541008   .5429384    -1.76   0.079    -2.018278    .1100767
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & agecat==45
(sum of wgt is   6.7098e+04)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     22,366
                                                F(14, 22365)      =      27.16
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0305
                                                Root MSE          =     .38248

                               (Std. Err. adjusted for 22,366 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0255372   .0090957     2.81   0.005     .0077091    .0433654
         t3_2 |   .0186757   .0094196     1.98   0.047     .0002127    .0371387
          age |   -.092768   .0451986    -2.05   0.040    -.1813604   -.0041756
         age2 |   .0961104   .0457613     2.10   0.036      .006415    .1858057
 d_race_black |  -.0316108   .0102544    -3.08   0.002    -.0517102   -.0115115
  d_race_hisp |  -.0497108   .0108888    -4.57   0.000    -.0710536   -.0283679
 d_race_other |  -.0526457   .0125108    -4.21   0.000    -.0771678   -.0281237
d_mar_married |    .110506   .0103141    10.71   0.000     .0902897    .1307223
d_mar_unknown |          0  (omitted)
d_gend_female |   .0199661   .0076013     2.63   0.009     .0050671    .0348652
      d_st_GA |  -.0018462   .0161484    -0.11   0.909    -.0334983    .0298058
      d_st_LA |   .0853063   .0210562     4.05   0.000     .0440347     .126578
      d_st_MI |  -.0849744   .0165887    -5.12   0.000    -.1174895   -.0524594
      d_st_NC |     .04701   .0192093     2.45   0.014     .0093584    .0846617
      d_st_TX |  -.0765349   .0141449    -5.41   0.000    -.1042599   -.0488099
        _cons |   2.442947   1.114145     2.19   0.028     .2591437     4.62675
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & agecat==55
No analysis for this combination
under55==1 & hhsize==1 & agecat==65
No analysis for this combination
under55==1 & hhsize==1 & agecat==75
No analysis for this combination
under55==1 & hhsize==1 & agecat==85
No analysis for this combination
under55==0 & hhsize==1 & agecat==17
No analysis for this combination
under55==0 & hhsize==1 & agecat==25
No analysis for this combination
under55==0 & hhsize==1 & agecat==35
No analysis for this combination
under55==0 & hhsize==1 & agecat==45
No analysis for this combination
under55==0 & hhsize==1 & agecat==55
(sum of wgt is   3.7858e+04)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     18,929
                                                F(13, 18928)      =      22.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0441
                                                Root MSE          =     .41218

                               (Std. Err. adjusted for 18,929 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .004362   .0098457     0.44   0.658    -.0149364    .0236605
         t3_2 |          0  (omitted)
          age |   .0177799   .0825797     0.22   0.830    -.1440837    .1796436
         age2 |  -.0090631    .069707    -0.13   0.897     -.145695    .1275689
 d_race_black |  -.0108294   .0147772    -0.73   0.464     -.039794    .0181351
  d_race_hisp |  -.0277798   .0156545    -1.77   0.076     -.058464    .0029044
 d_race_other |  -.0636633   .0181904    -3.50   0.000    -.0993181   -.0280085
d_mar_married |   .0942162   .0162934     5.78   0.000     .0622797    .1261527
d_mar_unknown |          0  (omitted)
d_gend_female |   .0448022   .0115833     3.87   0.000     .0220978    .0675065
      d_st_GA |  -.0507285    .023743    -2.14   0.033    -.0972669     -.00419
      d_st_LA |   .1376579   .0316068     4.36   0.000     .0757056    .1996101
      d_st_MI |  -.1290198    .023861    -5.41   0.000    -.1757893   -.0822502
      d_st_NC |   .0405265   .0271302     1.49   0.135    -.0126512    .0937041
      d_st_TX |   -.116652   .0211838    -5.51   0.000    -.1581741   -.0751299
        _cons |  -.4586696   2.441626    -0.19   0.851    -5.244475    4.327135
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & agecat==65
(sum of wgt is   1.7502e+04)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      8,751
                                                F(13, 8750)       =       9.30
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0346
                                                Root MSE          =     .44512

                                (Std. Err. adjusted for 8,751 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0123141   .0161124    -0.76   0.445    -.0438983      .01927
         t3_2 |          0  (omitted)
          age |   .5086325   .1561756     3.26   0.001     .2024916    .8147734
         age2 |  -.3659526   .1130167    -3.24   0.001    -.5874919   -.1444132
 d_race_black |  -.0338145   .0238922    -1.42   0.157    -.0806488    .0130199
  d_race_hisp |  -.0749479    .025208    -2.97   0.003    -.1243615   -.0255344
 d_race_other |  -.1311559   .0286562    -4.58   0.000    -.1873287    -.074983
d_mar_married |    .112724   .0264489     4.26   0.000      .060878      .16457
d_mar_unknown |          0  (omitted)
d_gend_female |    .036215   .0193902     1.87   0.062    -.0017944    .0742243
      d_st_GA |   .0039764   .0347565     0.11   0.909    -.0641545    .0721073
      d_st_LA |   .1616484   .0489251     3.30   0.001     .0657437     .257553
      d_st_MI |  -.0336947   .0392976    -0.86   0.391    -.1107272    .0433379
      d_st_NC |   .0859463   .0389129     2.21   0.027     .0096679    .1622247
      d_st_TX |  -.0376675   .0313577    -1.20   0.230     -.099136    .0238011
        _cons |  -17.33778   5.386799    -3.22   0.001    -27.89717   -6.778384
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & agecat==75
(sum of wgt is   5.7580e+03)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      2,879
                                                F(13, 2878)       =       5.14
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0556
                                                Root MSE          =     .41276

                                (Std. Err. adjusted for 2,879 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .026916   .0260157     1.03   0.301    -.0240953    .0779272
         t3_2 |          0  (omitted)
          age |   .1583234   .2717623     0.58   0.560    -.3745449    .6911918
         age2 |  -.1017696   .1715189    -0.59   0.553    -.4380819    .2345427
 d_race_black |  -.1235409   .0359997    -3.43   0.001    -.1941286   -.0529532
  d_race_hisp |  -.1363535   .0390493    -3.49   0.000     -.212921   -.0597861
 d_race_other |  -.1796822   .0413933    -4.34   0.000    -.2608456   -.0985188
d_mar_married |   .2010796    .051676     3.89   0.000     .0997538    .3024054
d_mar_unknown |          0  (omitted)
d_gend_female |   .0189927    .031812     0.60   0.551    -.0433838    .0813693
      d_st_GA |   .0303189   .0639275     0.47   0.635    -.0950295    .1556673
      d_st_LA |   .1146867   .0890177     1.29   0.198    -.0598583    .2892316
      d_st_MI |  -.1168054   .0618704    -1.89   0.059    -.2381201    .0045093
      d_st_NC |   .0887944   .0713317     1.24   0.213     -.051072    .2286608
      d_st_TX |  -.0417644   .0569753    -0.73   0.464    -.1534808    .0699521
        _cons |   -5.86253   10.75418    -0.55   0.586    -26.94921    15.22415
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & agecat==85
(sum of wgt is   1.2500e+03)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =        625
                                                F(12, 624)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0747
                                                Root MSE          =     .43498

                                  (Std. Err. adjusted for 625 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0399236   .0561285    -0.71   0.477    -.1501473    .0703001
         t3_2 |          0  (omitted)
          age |   2.737643   2.159324     1.27   0.205     -1.50278    6.978066
         age2 |  -1.561333   1.237485    -1.26   0.208    -3.991473    .8688064
 d_race_black |  -.1194447   .0681936    -1.75   0.080    -.2533615     .014472
  d_race_hisp |   -.174344   .0886804    -1.97   0.050    -.3484922   -.0001959
 d_race_other |  -.2152885   .0984146    -2.19   0.029    -.4085525   -.0220245
d_mar_married |   .2646673   .1366654     1.94   0.053    -.0037125     .533047
d_mar_unknown |          0  (omitted)
d_gend_female |   -.063911   .0777633    -0.82   0.411    -.2166205    .0887985
      d_st_GA |  -.2201645   .1442971    -1.53   0.128    -.5035312    .0632022
      d_st_LA |   .1842855   .1835969     1.00   0.316    -.1762572    .5448282
      d_st_MI |  -.2175423    .150669    -1.44   0.149    -.5134219    .0783373
      d_st_NC |  -.2020711   .1571697    -1.29   0.199    -.5107167    .1065744
      d_st_TX |  -.1511476   .1422129    -1.06   0.288    -.4304213    .1281262
        _cons |   -119.381   94.15329    -1.27   0.205    -304.2766    65.51473
-------------------------------------------------------------------------------
TableD3_ITTEstimatesByAgeCat_HH1Only.xls
dir : seeout

. restore

. 
. /*-----------------------
> TABLE D4: 
> ITT estimates by race
> among subjects in 1-person HH
> -----------------------*/
. 
. preserve

. 
. keep if never_voted == 1
(394 observations deleted)

. local treat_vars = " t3_1 t3_2 "

. 
. forvalues u = 1(-1)0 {
  2. foreach a in "black" "hispanic" "white" "other" {
  3. 
.         * define analysis sample condition
.         local select = "under55==`u' & hhsize==1"
  4.         di "`select' & r_race==`a'"
  5. 
.         * define ipw to use
.         local ipw = "ipw_t3_hh1_race_nv"
  6.                 
.         * define dummy predictors (excl race)
.         local d_vars = "d_st_GA d_st_LA d_st_MI d_st_NC d_st_TX d_mar_married d_mar_unknown d_gend_
> female"
  7.         
.                         if (`u' == 1) {                 // UNDER 55 ANALYSIS
  8.                                 
.                         if ("`a'" == "black") {
  9.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss `d_vars' [aweight=`ipw'] if `sel
> ect' & r_race=="`a'", vce(cluster hhid)
 10.                         local adjr2 = e(r2_a)
 11.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 12.                         local c_turnout = r(mean)
 13.                         outreg2 using "TableD4_ITTEstimatesByRace_HH1Only.xls", se bracket dec(3
> ) label ctitle("Under 55,Experiment,Race=`a'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) replace
 14.                         }
 15.                         else {
 16.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss `d_vars' [aweight=`ipw'] if `sel
> ect' & r_race=="`a'", vce(cluster hhid)
 17.                         local adjr2 = e(r2_a)
 18.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 19.                         local c_turnout = r(mean)
 20.                         outreg2 using "TableD4_ITTEstimatesByRace_HH1Only.xls", se bracket dec(3
> ) label ctitle("Under 55,Experiment,Race=`a'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 21.                         }
 22.                         
.                 }
 23.                 else {                                  // OVER 55 ANALYSIS
 24.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss `d_vars' [aweight=`ipw'] if `sel
> ect' & r_race=="`a'", vce(cluster hhid)
 25.                         local adjr2 = e(r2_a)
 26.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 27.                         local c_turnout = r(mean)
 28.                         outreg2 using "TableD4_ITTEstimatesByRace_HH1Only.xls", se bracket dec(3
> ) label ctitle("Over 55,Experiment,Race=`a'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 29.                                         
.                 }
 30. 
. }
 31. }       
under55==1 & hhsize==1 & r_race==black
(sum of wgt is   1.9447e+05)

Linear regression                               Number of obs     =     64,824
                                                F(13, 64823)      =      85.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0330
                                                Root MSE          =      .3471

                               (Std. Err. adjusted for 64,824 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0051779    .004861     1.07   0.287    -.0043496    .0147055
         t3_2 |   .0046877   .0050428     0.93   0.353    -.0051962    .0145715
          age |  -.0048449   .0013016    -3.72   0.000    -.0073961   -.0022938
         age2 |    .010487   .0019536     5.37   0.000      .006658    .0143159
     age_miss |   .1848054   .0835148     2.21   0.027     .0211164    .3484945
      d_st_GA |  -.0017731   .0069069    -0.26   0.797    -.0153106    .0117644
      d_st_LA |   .0766901    .009006     8.52   0.000     .0590383    .0943419
      d_st_MI |  -.0617673   .0079015    -7.82   0.000    -.0772541   -.0462804
      d_st_NC |    .015421   .0081274     1.90   0.058    -.0005088    .0313508
      d_st_TX |  -.0654689   .0064118   -10.21   0.000     -.078036   -.0529018
d_mar_married |   .1219409   .0087163    13.99   0.000     .1048569    .1390248
d_mar_unknown |   .2104099   .0969672     2.17   0.030     .0203542    .4004656
d_gend_female |   .0349977   .0035725     9.80   0.000     .0279955    .0419999
        _cons |   .1735868   .0208434     8.33   0.000     .1327338    .2144398
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & r_race==hispanic
(sum of wgt is   1.6818e+05)

Linear regression                               Number of obs     =     56,061
                                                F(13, 56060)      =      53.10
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0263
                                                Root MSE          =     .28927

                               (Std. Err. adjusted for 56,061 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0090461   .0043238     2.09   0.036     .0005715    .0175207
         t3_2 |   .0092263   .0044866     2.06   0.040     .0004325    .0180202
          age |  -.0012844   .0011941    -1.08   0.282    -.0036249    .0010562
         age2 |   .0056929   .0018389     3.10   0.002     .0020887    .0092972
     age_miss |  -.1592751   .0425607    -3.74   0.000    -.2426944   -.0758558
      d_st_GA |   .0089799   .0128889     0.70   0.486    -.0162824    .0342423
      d_st_LA |   .0710328    .022277     3.19   0.001     .0273697    .1146959
      d_st_MI |  -.0330318    .014588    -2.26   0.024    -.0616244   -.0044391
      d_st_NC |  -.0083091   .0129997    -0.64   0.523    -.0337885    .0171704
      d_st_TX |  -.0572335   .0104707    -5.47   0.000    -.0777561   -.0367109
d_mar_married |   .0617369   .0058592    10.54   0.000     .0502528     .073221
d_mar_unknown |   .6754492   .1166798     5.79   0.000     .4467561    .9041424
d_gend_female |   .0200754   .0031758     6.32   0.000     .0138507       .0263
        _cons |   .1003593   .0204623     4.90   0.000     .0602531    .1404655
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & r_race==white
(sum of wgt is   3.6509e+05)

Linear regression                               Number of obs     =    121,697
                                                F(13, 121696)     =      81.89
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0165
                                                Root MSE          =     .34841

                              (Std. Err. adjusted for 121,697 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0079453   .0035325     2.25   0.024     .0010217    .0148688
         t3_2 |   .0048918   .0036529     1.34   0.181    -.0022678    .0120514
          age |  -.0044662   .0010942    -4.08   0.000    -.0066108   -.0023217
         age2 |   .0101315   .0017211     5.89   0.000     .0067581    .0135048
     age_miss |   .1825528   .0639329     2.86   0.004     .0572454    .3078602
      d_st_GA |  -.0240892   .0062423    -3.86   0.000    -.0363239   -.0118545
      d_st_LA |   .0472589   .0094579     5.00   0.000     .0287215    .0657962
      d_st_MI |  -.0917344   .0049482   -18.54   0.000    -.1014328   -.0820359
      d_st_NC |  -.0178859   .0058685    -3.05   0.002     -.029388   -.0063839
      d_st_TX |  -.0655816   .0047731   -13.74   0.000    -.0749367   -.0562264
d_mar_married |   .0737435   .0072255    10.21   0.000     .0595817    .0879052
d_mar_unknown |   .1130202   .0651393     1.74   0.083    -.0146517    .2406922
d_gend_female |   .0027794    .002909     0.96   0.339    -.0029221     .008481
        _cons |    .225476   .0166097    13.57   0.000     .1929212    .2580308
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & r_race==other
(sum of wgt is   5.0361e+04)

Linear regression                               Number of obs     =     16,787
                                                F(13, 16786)      =      27.97
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0383
                                                Root MSE          =     .32943

                               (Std. Err. adjusted for 16,787 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0381825   .0086554     4.41   0.000     .0212171     .055148
         t3_2 |   .0204322   .0089451     2.28   0.022     .0028988    .0379656
          age |   .0021533   .0022125     0.97   0.330    -.0021834      .00649
         age2 |   .0007844    .003288     0.24   0.811    -.0056604    .0072292
     age_miss |    .226532   .1742956     1.30   0.194    -.1151057    .5681697
      d_st_GA |   .0018125   .0164579     0.11   0.912    -.0304467    .0340717
      d_st_LA |   .1398763   .0274032     5.10   0.000      .086163    .1935895
      d_st_MI |  -.0040157   .0165576    -0.24   0.808    -.0364704    .0284389
      d_st_NC |   .0556727   .0193808     2.87   0.004     .0176843    .0936612
      d_st_TX |  -.0461711   .0145937    -3.16   0.002    -.0747763    -.017566
d_mar_married |   .0823157   .0108968     7.55   0.000     .0609569    .1036746
d_mar_unknown |   .3590997   .2285839     1.57   0.116    -.0889489    .8071483
d_gend_female |  -.0114639   .0064372    -1.78   0.075    -.0240816    .0011537
        _cons |    .037999    .037833     1.00   0.315    -.0361577    .1121557
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & r_race==black
(sum of wgt is   1.9484e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      9,742
                                                F(10, 9741)       =      25.74
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0656
                                                Root MSE          =     .42964

                                (Std. Err. adjusted for 9,742 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0149706   .0142889     1.05   0.295    -.0130386    .0429799
         t3_2 |          0  (omitted)
          age |   .0398408   .0150676     2.64   0.008     .0103052    .0693764
         age2 |  -.0287879   .0111404    -2.58   0.010    -.0506255   -.0069503
     age_miss |          0  (omitted)
      d_st_GA |  -.0452988   .0264271    -1.71   0.087    -.0971015    .0065039
      d_st_LA |   .1694688    .034035     4.98   0.000     .1027531    .2361845
      d_st_MI |  -.1427989   .0315191    -4.53   0.000    -.2045829    -.081015
      d_st_NC |   .1118266   .0337825     3.31   0.001     .0456059    .1780473
      d_st_TX |  -.1198616   .0254164    -4.72   0.000     -.169683   -.0700403
d_mar_married |   .1371018   .0220548     6.22   0.000     .0938698    .1803339
d_mar_unknown |          0  (omitted)
d_gend_female |   .0699277   .0144584     4.84   0.000     .0415862    .0982692
        _cons |  -1.114564   .5037064    -2.21   0.027    -2.101933   -.1271947
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & r_race==hispanic
(sum of wgt is   1.5510e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      7,755
                                                F(10, 7754)       =      10.19
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0364
                                                Root MSE          =     .39405

                                (Std. Err. adjusted for 7,755 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   -.014908   .0151132    -0.99   0.324    -.0445339    .0147179
         t3_2 |          0  (omitted)
          age |   .0387563   .0156172     2.48   0.013     .0081423    .0693704
         age2 |   -.026985   .0115611    -2.33   0.020    -.0496479   -.0043221
     age_miss |          0  (omitted)
      d_st_GA |   .0406214     .06554     0.62   0.535    -.0878546    .1690974
      d_st_LA |   .4448451    .090754     4.90   0.000     .2669428    .6227474
      d_st_MI |   .0590579   .0780511     0.76   0.449    -.0939433     .212059
      d_st_NC |   .0476341   .0703228     0.68   0.498    -.0902175    .1854857
      d_st_TX |  -.0410755   .0572544    -0.72   0.473    -.1533095    .0711586
d_mar_married |   .1040934   .0200844     5.18   0.000     .0647224    .1434643
d_mar_unknown |          0  (omitted)
d_gend_female |   .0245909   .0150341     1.64   0.102      -.00488    .0540618
        _cons |  -1.159537   .5307002    -2.18   0.029    -2.199853   -.1192212
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & r_race==white
(sum of wgt is   2.0996e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity
note: d_gend_female omitted because of collinearity

Linear regression                               Number of obs     =     10,498
                                                F(8, 10497)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0187
                                                Root MSE          =     .44619

                               (Std. Err. adjusted for 10,498 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0012668   .0144819    -0.09   0.930    -.0296541    .0271206
         t3_2 |          0  (omitted)
          age |   .0497757   .0128625     3.87   0.000     .0245628    .0749886
         age2 |  -.0334734   .0093656    -3.57   0.000    -.0518318    -.015115
     age_miss |          0  (omitted)
      d_st_GA |  -.0242209   .0336684    -0.72   0.472    -.0902175    .0417756
      d_st_LA |   .0015743   .0426295     0.04   0.971    -.0819877    .0851362
      d_st_MI |  -.1168197   .0284472    -4.11   0.000    -.1725817   -.0610578
      d_st_NC |   .0121022   .0319063     0.38   0.704    -.0504403    .0746446
      d_st_TX |  -.0738746   .0266328    -2.77   0.006      -.12608   -.0216692
d_mar_married |   .7233205   .0237673    30.43   0.000     .6767321     .769909
d_mar_unknown |          0  (omitted)
d_gend_female |          0  (omitted)
        _cons |  -1.458778    .436017    -3.35   0.001    -2.313454   -.6041022
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & r_race==other
(sum of wgt is   6.3780e+03)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      3,189
                                                F(10, 3188)       =       3.49
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0475
                                                Root MSE          =     .37319

                                (Std. Err. adjusted for 3,189 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0012096   .0218616    -0.06   0.956    -.0440738    .0416546
         t3_2 |          0  (omitted)
          age |   .0284723   .0215672     1.32   0.187    -.0138147    .0707594
         age2 |  -.0206921   .0158936    -1.30   0.193    -.0518547    .0104705
     age_miss |          0  (omitted)
      d_st_GA |    .024978   .0582763     0.43   0.668    -.0892848    .1392409
      d_st_LA |   .3629377   .0970837     3.74   0.000     .1725849    .5532904
      d_st_MI |  -.0060582   .0586473    -0.10   0.918    -.1210485    .1089321
      d_st_NC |    .086088   .0664227     1.30   0.195    -.0441476    .2163236
      d_st_TX |  -.0319627   .0515473    -0.62   0.535    -.1330318    .0691065
d_mar_married |   .0692854   .0298464     2.32   0.020     .0107654    .1278054
d_mar_unknown |          0  (omitted)
d_gend_female |  -.0108238    .022013    -0.49   0.623     -.053985    .0323373
        _cons |  -.7982515   .7244926    -1.10   0.271     -2.21877    .6222672
-------------------------------------------------------------------------------
TableD4_ITTEstimatesByRace_HH1Only.xls
dir : seeout

. 
. restore

. 
. /*-----------------------
> TABLE D5: 
> ITT estimates by gender
> among subjects in 1-person HH
> -----------------------*/
. preserve

. 
. keep if never_voted == 1
(394 observations deleted)

. local treat_vars = " t3_1 t3_2 "

. 
. forvalues u = 1(-1)0 {
  2. foreach a in "female" "not_female" {
  3. 
.                 * define analysis sample condition
.                 local select = "under55==`u' & hhsize==1"
  4.                 di "`select' & r_gender==`a'"
  5.                 * define ipw to use
.                 local ipw = "ipw_t3_hh1_gender_nv"
  6.                 * define dummy predictors (excl gender)
.                 local d_vars = "d_st_GA d_st_LA d_st_MI d_st_NC d_st_TX d_mar_married d_mar_unknown
>  d_race_black d_race_hisp d_race_other"
  7.                 
.                 if (`u' == 1) {                 // UNDER 55 ANALYSIS
  8.                                 
.                         if ("`a'" == "female") {
  9.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss `d_vars' [aweight=`ipw'] if `sel
> ect' & r_gender=="`a'", vce(cluster hhid)
 10.                         local adjr2 = e(r2_a)
 11.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 12.                         local c_turnout = r(mean)
 13.                         outreg2 using "TableD5_ITTEstimatesByGender_HH1Only.xls", se bracket dec
> (3) label ctitle("Under 55,Experiment,`a'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) replace
 14.                         }
 15.                         else {
 16.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss `d_vars' [aweight=`ipw'] if `sel
> ect' & r_gender=="`a'", vce(cluster hhid)
 17.                         local adjr2 = e(r2_a)
 18.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 19.                         local c_turnout = r(mean)
 20.                         outreg2 using "TableD5_ITTEstimatesByGender_HH1Only.xls", se bracket dec
> (3) label ctitle("Under 55,Experiment,`a'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 21.                         }
 22.                         
.                 }
 23.                 else {                                  // OVER 55 ANALYSIS
 24.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss `d_vars' [aweight=`ipw'] if `sel
> ect' & r_gender=="`a'", vce(cluster hhid)
 25.                         local adjr2 = e(r2_a)
 26.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 27.                         local c_turnout = r(mean)
 28.                         outreg2 using "TableD5_ITTEstimatesByGender_HH1Only.xls", se bracket dec
> (3) label ctitle("Over 55,Experiment,`a'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 29.                                 
.                 }               
 30.                 
. }
 31. }
under55==1 & hhsize==1 & r_gender==female
(sum of wgt is   4.7306e+05)

Linear regression                               Number of obs     =    157,687
                                                F(15, 157686)     =     137.81
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0250
                                                Root MSE          =     .34397

                              (Std. Err. adjusted for 157,687 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0105793   .0030591     3.46   0.001     .0045836     .016575
         t3_2 |   .0080365   .0031687     2.54   0.011     .0018259    .0142471
          age |   -.002452   .0008444    -2.90   0.004    -.0041071    -.000797
         age2 |    .007208   .0012909     5.58   0.000     .0046778    .0097381
     age_miss |   .1524663   .0620851     2.46   0.014     .0307809    .2741517
      d_st_GA |  -.0138776   .0055966    -2.48   0.013    -.0248467   -.0029085
      d_st_LA |   .0633345   .0078326     8.09   0.000     .0479828    .0786863
      d_st_MI |  -.0782374   .0052118   -15.01   0.000    -.0884525   -.0680223
      d_st_NC |  -.0071155   .0059438    -1.20   0.231    -.0187652    .0045342
      d_st_TX |  -.0706883   .0047428   -14.90   0.000    -.0799841   -.0613924
d_mar_married |   .0877741   .0047942    18.31   0.000     .0783776    .0971707
d_mar_unknown |   .1696926   .0666252     2.55   0.011     .0391087    .3002765
 d_race_black |   -.011311   .0030522    -3.71   0.000    -.0172933   -.0053288
  d_race_hisp |  -.0412934   .0029599   -13.95   0.000    -.0470947   -.0354922
 d_race_other |  -.0421649   .0047551    -8.87   0.000    -.0514848    -.032845
        _cons |   .1913341   .0135318    14.14   0.000     .1648121    .2178561
-------------------------------------------------------------------------------
TableD5_ITTEstimatesByGender_HH1Only.xls
dir : seeout
under55==1 & hhsize==1 & r_gender==not_female
(sum of wgt is   3.0505e+05)

Linear regression                               Number of obs     =    101,682
                                                F(15, 101681)     =      95.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0259
                                                Root MSE          =     .32108

                              (Std. Err. adjusted for 101,682 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .007512   .0035758     2.10   0.036     .0005034    .0145206
         t3_2 |   .0049408   .0037028     1.33   0.182    -.0023166    .0121982
          age |  -.0052156   .0010408    -5.01   0.000    -.0072556   -.0031756
         age2 |   .0112522   .0015913     7.07   0.000     .0081332    .0143712
     age_miss |   .1996816   .0738138     2.71   0.007     .0550075    .3443556
      d_st_GA |  -.0114588   .0062179    -1.84   0.065    -.0236457    .0007282
      d_st_LA |   .0648534   .0093693     6.92   0.000     .0464897     .083217
      d_st_MI |  -.0779449   .0057311   -13.60   0.000    -.0891777   -.0667121
      d_st_NC |  -.0005658   .0064613    -0.09   0.930    -.0132298    .0120983
      d_st_TX |  -.0565989   .0051926   -10.90   0.000    -.0667763   -.0464215
d_mar_married |   .0711982   .0062851    11.33   0.000     .0588796    .0835169
d_mar_unknown |   .1519611   .0800212     1.90   0.058    -.0048795    .3088016
 d_race_black |  -.0415244   .0037769   -10.99   0.000    -.0489272   -.0341217
  d_race_hisp |   -.061585   .0036894   -16.69   0.000    -.0688161   -.0543538
 d_race_other |  -.0287234   .0055782    -5.15   0.000    -.0396565   -.0177903
        _cons |    .225453    .016123    13.98   0.000     .1938521    .2570538
-------------------------------------------------------------------------------
TableD5_ITTEstimatesByGender_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & r_gender==female
(sum of wgt is   4.1560e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     20,780
                                                F(12, 20779)      =      28.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0406
                                                Root MSE          =     .43222

                               (Std. Err. adjusted for 20,780 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0046854   .0099029    -0.47   0.636    -.0240958    .0147249
         t3_2 |          0  (omitted)
          age |   .0499464   .0092055     5.43   0.000     .0319029      .06799
         age2 |  -.0346707   .0067343    -5.15   0.000    -.0478706   -.0214709
     age_miss |          0  (omitted)
      d_st_GA |  -.0072532   .0233056    -0.31   0.756     -.052934    .0384276
      d_st_LA |   .1410618   .0317107     4.45   0.000     .0789064    .2032172
      d_st_MI |  -.0963598   .0226493    -4.25   0.000    -.1407542   -.0519654
      d_st_NC |   .0561616   .0249184     2.25   0.024     .0073196    .1050036
      d_st_TX |  -.0716569     .02021    -3.55   0.000    -.1112701   -.0320436
d_mar_married |   .1584371   .0197782     8.01   0.000     .1196702     .197204
d_mar_unknown |          0  (omitted)
 d_race_black |  -.0262309   .0130869    -2.00   0.045    -.0518823   -.0005795
  d_race_hisp |  -.0767538   .0142283    -5.39   0.000    -.1046423   -.0488653
 d_race_other |  -.1401055    .017376    -8.06   0.000    -.1741638   -.1060472
        _cons |  -1.435668   .3109196    -4.62   0.000    -2.045095   -.8262414
-------------------------------------------------------------------------------
TableD5_ITTEstimatesByGender_HH1Only.xls
dir : seeout
under55==0 & hhsize==1 & r_gender==not_female
(sum of wgt is   2.0808e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     10,404
                                                F(11, 10403)      =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0427
                                                Root MSE          =     .40095

                               (Std. Err. adjusted for 10,404 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0097698   .0133393     0.73   0.464    -.0163778    .0359175
         t3_2 |          0  (omitted)
          age |   .0125659   .0145503     0.86   0.388    -.0159556    .0410874
         age2 |  -.0076759   .0108132    -0.71   0.478    -.0288718      .01352
     age_miss |          0  (omitted)
      d_st_GA |  -.0782372   .0319349    -2.45   0.014    -.1408358   -.0156385
      d_st_LA |   .1478011   .0431906     3.42   0.001     .0631393    .2324629
      d_st_MI |  -.1041653   .0382067    -2.73   0.006    -.1790577   -.0292728
      d_st_NC |   .0483876   .0398001     1.22   0.224    -.0296283    .1264036
      d_st_TX |  -.1356142    .030206    -4.49   0.000    -.1948238   -.0764046
d_mar_married |   .0634803    .017867     3.55   0.000     .0284575    .0985032
d_mar_unknown |          0  (omitted)
 d_race_black |  -.7415902   .0220921   -33.57   0.000    -.7848951   -.6982854
  d_race_hisp |  -.7292934   .0258895   -28.17   0.000    -.7800418    -.678545
 d_race_other |  -.7601667    .027314   -27.83   0.000    -.8137075   -.7066259
        _cons |    .534382   .4814294     1.11   0.267    -.4093122    1.478076
-------------------------------------------------------------------------------
TableD5_ITTEstimatesByGender_HH1Only.xls
dir : seeout

. 
. restore

. 
. /*-----------------------
> FIGURE D1:
> Summary figure of 
>  conditional ITT effects
>  by demographic subgroup
>  among subjects in 1-person HH
> -----------------------*/
. local treatvars = "t3_1 t3_2"

. 
. * By Age
. foreach u in 1 0 {
  2. if(`u' == 1){
  3. foreach a in 17 25 35 45 {
  4. reg voted14 `treatvars' age age2 d_race_black d_race_hisp d_race_other d_mar_married d_mar_unkno
> wn d_gend_female d_st_GA d_st_LA d_st_MI d_st_NC d_st_TX [aweight=ipw_t3_hh1_age_nv] if under55==`u
> ' & hhsize == 1 & agecat==`a' & never_voted ==1, vce(cluster hhid)
  5. estimates store u55_`u'_agecat_`a'
  6. }
  7. }
  8. else{
  9. foreach a in 55 65 75 85 {
 10. reg voted14 `treatvars' age age2 d_race_black d_race_hisp d_race_other d_mar_married d_mar_unkno
> wn d_gend_female d_st_GA d_st_LA d_st_MI d_st_NC d_st_TX [aweight=ipw_t3_hh1_age_nv] if under55==`u
> ' & hhsize == 1 & agecat==`a', vce(cluster hhid)
 11. estimates store u55_`u'_agecat_`a'
 12. }
 13. }
 14. }
(sum of wgt is   4.0352e+05)

Linear regression                               Number of obs     =    134,508
                                                F(15, 134507)     =     117.05
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0211
                                                Root MSE          =     .31732

                              (Std. Err. adjusted for 134,508 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0065958    .003046     2.17   0.030     .0006258    .0125658
         t3_2 |   .0067932   .0031625     2.15   0.032     .0005947    .0129917
          age |  -.2279164   .0149587   -15.24   0.000    -.2572352   -.1985975
         age2 |   .5209152   .0357665    14.56   0.000     .4508136    .5910168
 d_race_black |  -.0176694   .0030322    -5.83   0.000    -.0236124   -.0117263
  d_race_hisp |  -.0461336   .0028193   -16.36   0.000    -.0516594   -.0406079
 d_race_other |  -.0353675   .0057763    -6.12   0.000     -.046689   -.0240459
d_mar_married |    .011933   .0065967     1.81   0.070    -.0009964    .0248623
d_mar_unknown |   .1995963   .0843347     2.37   0.018      .034302    .3648907
d_gend_female |   .0108794   .0022922     4.75   0.000     .0063867     .015372
      d_st_GA |  -.0221327   .0053506    -4.14   0.000    -.0326198   -.0116457
      d_st_LA |   .0478175   .0082058     5.83   0.000     .0317342    .0639008
      d_st_MI |  -.0503004   .0050507    -9.96   0.000    -.0601997   -.0404011
      d_st_NC |  -.0247754   .0053957    -4.59   0.000    -.0353508      -.0142
      d_st_TX |  -.0698408   .0044762   -15.60   0.000    -.0786142   -.0610675
        _cons |   2.619407   .1552631    16.87   0.000     2.315094    2.923719
-------------------------------------------------------------------------------
(sum of wgt is   2.0381e+05)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     67,938
                                                F(14, 67937)      =      76.16
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0281
                                                Root MSE          =     .33379

                               (Std. Err. adjusted for 67,938 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0131204   .0045109     2.91   0.004      .004279    .0219618
         t3_2 |   .0056773   .0046617     1.22   0.223    -.0034597    .0148143
          age |   .0442292   .0132283     3.34   0.001     .0183019    .0701566
         age2 |  -.0716914   .0226095    -3.17   0.002    -.1160061   -.0273767
 d_race_black |  -.0351009   .0045908    -7.65   0.000    -.0440989   -.0261028
  d_race_hisp |  -.0568525   .0045566   -12.48   0.000    -.0657834   -.0479216
 d_race_other |  -.0508462   .0060427    -8.41   0.000    -.0626899   -.0390025
d_mar_married |   .0894954    .006378    14.03   0.000     .0769945    .1019962
d_mar_unknown |          0  (omitted)
d_gend_female |   .0170076   .0035013     4.86   0.000      .010145    .0238702
      d_st_GA |   .0054004    .008343     0.65   0.517    -.0109518    .0217526
      d_st_LA |   .0913865    .011347     8.05   0.000     .0691464    .1136267
      d_st_MI |  -.0845545   .0073876   -11.45   0.000    -.0990343   -.0700748
      d_st_NC |   .0051847   .0093582     0.55   0.580    -.0131574    .0235268
      d_st_TX |  -.0486027   .0070618    -6.88   0.000    -.0624438   -.0347615
        _cons |  -.5130807   .1918462    -2.67   0.007    -.8890991   -.1370624
-------------------------------------------------------------------------------
(sum of wgt is   1.0215e+05)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     34,051
                                                F(14, 34050)      =      37.53
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0299
                                                Root MSE          =     .36382

                               (Std. Err. adjusted for 34,051 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .002745   .0071667     0.38   0.702     -.011302     .016792
         t3_2 |  -.0000261   .0073893    -0.00   0.997    -.0145095    .0144572
          age |   .0565278   .0277638     2.04   0.042     .0021098    .1109458
         age2 |  -.0694635   .0353131    -1.97   0.049    -.1386783   -.0002487
 d_race_black |  -.0196628   .0082132    -2.39   0.017    -.0357609   -.0035647
  d_race_hisp |  -.0360399   .0083153    -4.33   0.000    -.0523381   -.0197416
 d_race_other |  -.0137228   .0094936    -1.45   0.148    -.0323306     .004885
d_mar_married |    .100224   .0082764    12.11   0.000      .084002    .1164459
d_mar_unknown |          0  (omitted)
d_gend_female |   .0233655   .0059476     3.93   0.000     .0117079     .035023
      d_st_GA |   .0195222   .0135538     1.44   0.150    -.0070437    .0460881
      d_st_LA |   .0965609   .0185277     5.21   0.000     .0602459    .1328758
      d_st_MI |  -.0889346   .0134122    -6.63   0.000    -.1152229   -.0626463
      d_st_NC |   .0269206   .0157671     1.71   0.088    -.0039836    .0578247
      d_st_TX |  -.0700042   .0118295    -5.92   0.000    -.0931903   -.0468181
        _cons |  -.9541008   .5429384    -1.76   0.079    -2.018278    .1100767
-------------------------------------------------------------------------------
(sum of wgt is   6.7098e+04)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     22,366
                                                F(14, 22365)      =      27.16
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0305
                                                Root MSE          =     .38248

                               (Std. Err. adjusted for 22,366 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0255372   .0090957     2.81   0.005     .0077091    .0433654
         t3_2 |   .0186757   .0094196     1.98   0.047     .0002127    .0371387
          age |   -.092768   .0451986    -2.05   0.040    -.1813604   -.0041756
         age2 |   .0961104   .0457613     2.10   0.036      .006415    .1858057
 d_race_black |  -.0316108   .0102544    -3.08   0.002    -.0517102   -.0115115
  d_race_hisp |  -.0497108   .0108888    -4.57   0.000    -.0710536   -.0283679
 d_race_other |  -.0526457   .0125108    -4.21   0.000    -.0771678   -.0281237
d_mar_married |    .110506   .0103141    10.71   0.000     .0902897    .1307223
d_mar_unknown |          0  (omitted)
d_gend_female |   .0199661   .0076013     2.63   0.009     .0050671    .0348652
      d_st_GA |  -.0018462   .0161484    -0.11   0.909    -.0334983    .0298058
      d_st_LA |   .0853063   .0210562     4.05   0.000     .0440347     .126578
      d_st_MI |  -.0849744   .0165887    -5.12   0.000    -.1174895   -.0524594
      d_st_NC |     .04701   .0192093     2.45   0.014     .0093584    .0846617
      d_st_TX |  -.0765349   .0141449    -5.41   0.000    -.1042599   -.0488099
        _cons |   2.442947   1.114145     2.19   0.028     .2591437     4.62675
-------------------------------------------------------------------------------
(sum of wgt is   3.7858e+04)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     18,929
                                                F(13, 18928)      =      22.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0441
                                                Root MSE          =     .41218

                               (Std. Err. adjusted for 18,929 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .004362   .0098457     0.44   0.658    -.0149364    .0236605
         t3_2 |          0  (omitted)
          age |   .0177799   .0825797     0.22   0.830    -.1440837    .1796436
         age2 |  -.0090631    .069707    -0.13   0.897     -.145695    .1275689
 d_race_black |  -.0108294   .0147772    -0.73   0.464     -.039794    .0181351
  d_race_hisp |  -.0277798   .0156545    -1.77   0.076     -.058464    .0029044
 d_race_other |  -.0636633   .0181904    -3.50   0.000    -.0993181   -.0280085
d_mar_married |   .0942162   .0162934     5.78   0.000     .0622797    .1261527
d_mar_unknown |          0  (omitted)
d_gend_female |   .0448022   .0115833     3.87   0.000     .0220978    .0675065
      d_st_GA |  -.0507285    .023743    -2.14   0.033    -.0972669     -.00419
      d_st_LA |   .1376579   .0316068     4.36   0.000     .0757056    .1996101
      d_st_MI |  -.1290198    .023861    -5.41   0.000    -.1757893   -.0822502
      d_st_NC |   .0405265   .0271302     1.49   0.135    -.0126512    .0937041
      d_st_TX |   -.116652   .0211838    -5.51   0.000    -.1581741   -.0751299
        _cons |  -.4586696   2.441626    -0.19   0.851    -5.244475    4.327135
-------------------------------------------------------------------------------
(sum of wgt is   1.7502e+04)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      8,751
                                                F(13, 8750)       =       9.30
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0346
                                                Root MSE          =     .44512

                                (Std. Err. adjusted for 8,751 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0123141   .0161124    -0.76   0.445    -.0438983      .01927
         t3_2 |          0  (omitted)
          age |   .5086325   .1561756     3.26   0.001     .2024916    .8147734
         age2 |  -.3659526   .1130167    -3.24   0.001    -.5874919   -.1444132
 d_race_black |  -.0338145   .0238922    -1.42   0.157    -.0806488    .0130199
  d_race_hisp |  -.0749479    .025208    -2.97   0.003    -.1243615   -.0255344
 d_race_other |  -.1311559   .0286562    -4.58   0.000    -.1873287    -.074983
d_mar_married |    .112724   .0264489     4.26   0.000      .060878      .16457
d_mar_unknown |          0  (omitted)
d_gend_female |    .036215   .0193902     1.87   0.062    -.0017944    .0742243
      d_st_GA |   .0039764   .0347565     0.11   0.909    -.0641545    .0721073
      d_st_LA |   .1616484   .0489251     3.30   0.001     .0657437     .257553
      d_st_MI |  -.0336947   .0392976    -0.86   0.391    -.1107272    .0433379
      d_st_NC |   .0859463   .0389129     2.21   0.027     .0096679    .1622247
      d_st_TX |  -.0376675   .0313577    -1.20   0.230     -.099136    .0238011
        _cons |  -17.33778   5.386799    -3.22   0.001    -27.89717   -6.778384
-------------------------------------------------------------------------------
(sum of wgt is   5.7580e+03)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      2,879
                                                F(13, 2878)       =       5.14
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0556
                                                Root MSE          =     .41276

                                (Std. Err. adjusted for 2,879 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .026916   .0260157     1.03   0.301    -.0240953    .0779272
         t3_2 |          0  (omitted)
          age |   .1583234   .2717623     0.58   0.560    -.3745449    .6911918
         age2 |  -.1017696   .1715189    -0.59   0.553    -.4380819    .2345427
 d_race_black |  -.1235409   .0359997    -3.43   0.001    -.1941286   -.0529532
  d_race_hisp |  -.1363535   .0390493    -3.49   0.000     -.212921   -.0597861
 d_race_other |  -.1796822   .0413933    -4.34   0.000    -.2608456   -.0985188
d_mar_married |   .2010796    .051676     3.89   0.000     .0997538    .3024054
d_mar_unknown |          0  (omitted)
d_gend_female |   .0189927    .031812     0.60   0.551    -.0433838    .0813693
      d_st_GA |   .0303189   .0639275     0.47   0.635    -.0950295    .1556673
      d_st_LA |   .1146867   .0890177     1.29   0.198    -.0598583    .2892316
      d_st_MI |  -.1168054   .0618704    -1.89   0.059    -.2381201    .0045093
      d_st_NC |   .0887944   .0713317     1.24   0.213     -.051072    .2286608
      d_st_TX |  -.0417644   .0569753    -0.73   0.464    -.1534808    .0699521
        _cons |   -5.86253   10.75418    -0.55   0.586    -26.94921    15.22415
-------------------------------------------------------------------------------
(sum of wgt is   1.2500e+03)
note: t3_2 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =        625
                                                F(12, 624)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0747
                                                Root MSE          =     .43498

                                  (Std. Err. adjusted for 625 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0399236   .0561285    -0.71   0.477    -.1501473    .0703001
         t3_2 |          0  (omitted)
          age |   2.737643   2.159324     1.27   0.205     -1.50278    6.978066
         age2 |  -1.561333   1.237485    -1.26   0.208    -3.991473    .8688064
 d_race_black |  -.1194447   .0681936    -1.75   0.080    -.2533615     .014472
  d_race_hisp |   -.174344   .0886804    -1.97   0.050    -.3484922   -.0001959
 d_race_other |  -.2152885   .0984146    -2.19   0.029    -.4085525   -.0220245
d_mar_married |   .2646673   .1366654     1.94   0.053    -.0037125     .533047
d_mar_unknown |          0  (omitted)
d_gend_female |   -.063911   .0777633    -0.82   0.411    -.2166205    .0887985
      d_st_GA |  -.2201645   .1442971    -1.53   0.128    -.5035312    .0632022
      d_st_LA |   .1842855   .1835969     1.00   0.316    -.1762572    .5448282
      d_st_MI |  -.2175423    .150669    -1.44   0.149    -.5134219    .0783373
      d_st_NC |  -.2020711   .1571697    -1.29   0.199    -.5107167    .1065744
      d_st_TX |  -.1511476   .1422129    -1.06   0.288    -.4304213    .1281262
        _cons |   -119.381   94.15329    -1.27   0.205    -304.2766    65.51473
-------------------------------------------------------------------------------

. 
. * By Race
. foreach u in 1 0 {
  2. foreach a in black white hispanic other {
  3. reg voted14 `treatvars' age age2 age_miss d_gend_female d_mar_married d_mar_unknown d_st_GA d_st
> _LA d_st_MI d_st_NC d_st_TX [aweight=ipw_t3_hh1_race_nv] if under55==`u' & hhsize==1 & never_voted=
> =1 & r_race=="`a'" , vce(cluster hhid)
  4. estimates store u55_`u'_race_`a'
  5. }
  6. }
(sum of wgt is   1.9447e+05)

Linear regression                               Number of obs     =     64,824
                                                F(13, 64823)      =      85.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0330
                                                Root MSE          =      .3471

                               (Std. Err. adjusted for 64,824 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0051779    .004861     1.07   0.287    -.0043496    .0147055
         t3_2 |   .0046877   .0050428     0.93   0.353    -.0051962    .0145715
          age |  -.0048449   .0013016    -3.72   0.000    -.0073961   -.0022938
         age2 |    .010487   .0019536     5.37   0.000      .006658    .0143159
     age_miss |   .1848054   .0835148     2.21   0.027     .0211164    .3484945
d_gend_female |   .0349977   .0035725     9.80   0.000     .0279955    .0419999
d_mar_married |   .1219409   .0087163    13.99   0.000     .1048569    .1390248
d_mar_unknown |   .2104099   .0969672     2.17   0.030     .0203542    .4004656
      d_st_GA |  -.0017731   .0069069    -0.26   0.797    -.0153106    .0117644
      d_st_LA |   .0766901    .009006     8.52   0.000     .0590383    .0943419
      d_st_MI |  -.0617673   .0079015    -7.82   0.000    -.0772541   -.0462804
      d_st_NC |    .015421   .0081274     1.90   0.058    -.0005088    .0313508
      d_st_TX |  -.0654689   .0064118   -10.21   0.000     -.078036   -.0529018
        _cons |   .1735868   .0208434     8.33   0.000     .1327338    .2144398
-------------------------------------------------------------------------------
(sum of wgt is   3.6509e+05)

Linear regression                               Number of obs     =    121,697
                                                F(13, 121696)     =      81.89
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0165
                                                Root MSE          =     .34841

                              (Std. Err. adjusted for 121,697 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0079453   .0035325     2.25   0.024     .0010217    .0148688
         t3_2 |   .0048918   .0036529     1.34   0.181    -.0022678    .0120514
          age |  -.0044662   .0010942    -4.08   0.000    -.0066108   -.0023217
         age2 |   .0101315   .0017211     5.89   0.000     .0067581    .0135048
     age_miss |   .1825528   .0639329     2.86   0.004     .0572454    .3078602
d_gend_female |   .0027794    .002909     0.96   0.339    -.0029221     .008481
d_mar_married |   .0737435   .0072255    10.21   0.000     .0595817    .0879052
d_mar_unknown |   .1130202   .0651393     1.74   0.083    -.0146517    .2406922
      d_st_GA |  -.0240892   .0062423    -3.86   0.000    -.0363239   -.0118545
      d_st_LA |   .0472589   .0094579     5.00   0.000     .0287215    .0657962
      d_st_MI |  -.0917344   .0049482   -18.54   0.000    -.1014328   -.0820359
      d_st_NC |  -.0178859   .0058685    -3.05   0.002     -.029388   -.0063839
      d_st_TX |  -.0655816   .0047731   -13.74   0.000    -.0749367   -.0562264
        _cons |    .225476   .0166097    13.57   0.000     .1929212    .2580308
-------------------------------------------------------------------------------
(sum of wgt is   1.6818e+05)

Linear regression                               Number of obs     =     56,061
                                                F(13, 56060)      =      53.10
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0263
                                                Root MSE          =     .28927

                               (Std. Err. adjusted for 56,061 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0090461   .0043238     2.09   0.036     .0005715    .0175207
         t3_2 |   .0092263   .0044866     2.06   0.040     .0004325    .0180202
          age |  -.0012844   .0011941    -1.08   0.282    -.0036249    .0010562
         age2 |   .0056929   .0018389     3.10   0.002     .0020887    .0092972
     age_miss |  -.1592751   .0425607    -3.74   0.000    -.2426944   -.0758558
d_gend_female |   .0200754   .0031758     6.32   0.000     .0138507       .0263
d_mar_married |   .0617369   .0058592    10.54   0.000     .0502528     .073221
d_mar_unknown |   .6754492   .1166798     5.79   0.000     .4467561    .9041424
      d_st_GA |   .0089799   .0128889     0.70   0.486    -.0162824    .0342423
      d_st_LA |   .0710328    .022277     3.19   0.001     .0273697    .1146959
      d_st_MI |  -.0330318    .014588    -2.26   0.024    -.0616244   -.0044391
      d_st_NC |  -.0083091   .0129997    -0.64   0.523    -.0337885    .0171704
      d_st_TX |  -.0572335   .0104707    -5.47   0.000    -.0777561   -.0367109
        _cons |   .1003593   .0204623     4.90   0.000     .0602531    .1404655
-------------------------------------------------------------------------------
(sum of wgt is   5.0361e+04)

Linear regression                               Number of obs     =     16,787
                                                F(13, 16786)      =      27.97
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0383
                                                Root MSE          =     .32943

                               (Std. Err. adjusted for 16,787 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0381825   .0086554     4.41   0.000     .0212171     .055148
         t3_2 |   .0204322   .0089451     2.28   0.022     .0028988    .0379656
          age |   .0021533   .0022125     0.97   0.330    -.0021834      .00649
         age2 |   .0007844    .003288     0.24   0.811    -.0056604    .0072292
     age_miss |    .226532   .1742956     1.30   0.194    -.1151057    .5681697
d_gend_female |  -.0114639   .0064372    -1.78   0.075    -.0240816    .0011537
d_mar_married |   .0823157   .0108968     7.55   0.000     .0609569    .1036746
d_mar_unknown |   .3590997   .2285839     1.57   0.116    -.0889489    .8071483
      d_st_GA |   .0018125   .0164579     0.11   0.912    -.0304467    .0340717
      d_st_LA |   .1398763   .0274032     5.10   0.000      .086163    .1935895
      d_st_MI |  -.0040157   .0165576    -0.24   0.808    -.0364704    .0284389
      d_st_NC |   .0556727   .0193808     2.87   0.004     .0176843    .0936612
      d_st_TX |  -.0461711   .0145937    -3.16   0.002    -.0747763    -.017566
        _cons |    .037999    .037833     1.00   0.315    -.0361577    .1121557
-------------------------------------------------------------------------------
(sum of wgt is   1.9484e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      9,742
                                                F(10, 9741)       =      25.74
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0656
                                                Root MSE          =     .42964

                                (Std. Err. adjusted for 9,742 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0149706   .0142889     1.05   0.295    -.0130386    .0429799
         t3_2 |          0  (omitted)
          age |   .0398408   .0150676     2.64   0.008     .0103052    .0693764
         age2 |  -.0287879   .0111404    -2.58   0.010    -.0506255   -.0069503
     age_miss |          0  (omitted)
d_gend_female |   .0699277   .0144584     4.84   0.000     .0415862    .0982692
d_mar_married |   .1371018   .0220548     6.22   0.000     .0938698    .1803339
d_mar_unknown |          0  (omitted)
      d_st_GA |  -.0452988   .0264271    -1.71   0.087    -.0971015    .0065039
      d_st_LA |   .1694688    .034035     4.98   0.000     .1027531    .2361845
      d_st_MI |  -.1427989   .0315191    -4.53   0.000    -.2045829    -.081015
      d_st_NC |   .1118266   .0337825     3.31   0.001     .0456059    .1780473
      d_st_TX |  -.1198616   .0254164    -4.72   0.000     -.169683   -.0700403
        _cons |  -1.114564   .5037064    -2.21   0.027    -2.101933   -.1271947
-------------------------------------------------------------------------------
(sum of wgt is   2.0996e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_married omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     10,498
                                                F(8, 10497)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0187
                                                Root MSE          =     .44619

                               (Std. Err. adjusted for 10,498 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0012668   .0144819    -0.09   0.930    -.0296541    .0271206
         t3_2 |          0  (omitted)
          age |   .0497757   .0128625     3.87   0.000     .0245628    .0749886
         age2 |  -.0334734   .0093656    -3.57   0.000    -.0518318    -.015115
     age_miss |          0  (omitted)
d_gend_female |  -.7233205   .0237673   -30.43   0.000     -.769909   -.6767321
d_mar_married |          0  (omitted)
d_mar_unknown |          0  (omitted)
      d_st_GA |  -.0242209   .0336684    -0.72   0.472    -.0902175    .0417756
      d_st_LA |   .0015743   .0426295     0.04   0.971    -.0819877    .0851362
      d_st_MI |  -.1168197   .0284472    -4.11   0.000    -.1725817   -.0610578
      d_st_NC |   .0121022   .0319063     0.38   0.704    -.0504403    .0746446
      d_st_TX |  -.0738746   .0266328    -2.77   0.006      -.12608   -.0216692
        _cons |  -.7354578   .4330448    -1.70   0.089    -1.584308    .1133923
-------------------------------------------------------------------------------
(sum of wgt is   1.5510e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      7,755
                                                F(10, 7754)       =      10.19
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0364
                                                Root MSE          =     .39405

                                (Std. Err. adjusted for 7,755 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   -.014908   .0151132    -0.99   0.324    -.0445339    .0147179
         t3_2 |          0  (omitted)
          age |   .0387563   .0156172     2.48   0.013     .0081423    .0693704
         age2 |   -.026985   .0115611    -2.33   0.020    -.0496479   -.0043221
     age_miss |          0  (omitted)
d_gend_female |   .0245909   .0150341     1.64   0.102      -.00488    .0540618
d_mar_married |   .1040934   .0200844     5.18   0.000     .0647224    .1434643
d_mar_unknown |          0  (omitted)
      d_st_GA |   .0406214     .06554     0.62   0.535    -.0878546    .1690974
      d_st_LA |   .4448451    .090754     4.90   0.000     .2669428    .6227474
      d_st_MI |   .0590579   .0780511     0.76   0.449    -.0939433     .212059
      d_st_NC |   .0476341   .0703228     0.68   0.498    -.0902175    .1854857
      d_st_TX |  -.0410755   .0572544    -0.72   0.473    -.1533095    .0711586
        _cons |  -1.159537   .5307002    -2.18   0.029    -2.199853   -.1192212
-------------------------------------------------------------------------------
(sum of wgt is   6.3780e+03)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      3,189
                                                F(10, 3188)       =       3.49
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0475
                                                Root MSE          =     .37319

                                (Std. Err. adjusted for 3,189 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0012096   .0218616    -0.06   0.956    -.0440738    .0416546
         t3_2 |          0  (omitted)
          age |   .0284723   .0215672     1.32   0.187    -.0138147    .0707594
         age2 |  -.0206921   .0158936    -1.30   0.193    -.0518547    .0104705
     age_miss |          0  (omitted)
d_gend_female |  -.0108238    .022013    -0.49   0.623     -.053985    .0323373
d_mar_married |   .0692854   .0298464     2.32   0.020     .0107654    .1278054
d_mar_unknown |          0  (omitted)
      d_st_GA |    .024978   .0582763     0.43   0.668    -.0892848    .1392409
      d_st_LA |   .3629377   .0970837     3.74   0.000     .1725849    .5532904
      d_st_MI |  -.0060582   .0586473    -0.10   0.918    -.1210485    .1089321
      d_st_NC |    .086088   .0664227     1.30   0.195    -.0441476    .2163236
      d_st_TX |  -.0319627   .0515473    -0.62   0.535    -.1330318    .0691065
        _cons |  -.7982515   .7244926    -1.10   0.271     -2.21877    .6222672
-------------------------------------------------------------------------------

.                                 
. * By Gender
. foreach u in 1 0 {
  2. foreach a in female not_female {
  3. reg voted14 `treatvars' age age2 age_miss d_race_black d_race_hisp d_race_other d_mar_married d_
> mar_unknown d_st_GA d_st_LA d_st_MI d_st_NC d_st_TX [aweight=ipw_t3_hh1_gender_nv] if under55==`u' 
> & hhsize==1 & never_voted==1 & r_gender=="`a'" , vce(cluster hhid)
  4. estimates store u55_`u'_gender_`a'
  5. }
  6. }
(sum of wgt is   4.7306e+05)

Linear regression                               Number of obs     =    157,687
                                                F(15, 157686)     =     137.81
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0250
                                                Root MSE          =     .34397

                              (Std. Err. adjusted for 157,687 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0105793   .0030591     3.46   0.001     .0045836     .016575
         t3_2 |   .0080365   .0031687     2.54   0.011     .0018259    .0142471
          age |   -.002452   .0008444    -2.90   0.004    -.0041071    -.000797
         age2 |    .007208   .0012909     5.58   0.000     .0046778    .0097381
     age_miss |   .1524663   .0620851     2.46   0.014     .0307809    .2741517
 d_race_black |   -.011311   .0030522    -3.71   0.000    -.0172933   -.0053288
  d_race_hisp |  -.0412934   .0029599   -13.95   0.000    -.0470947   -.0354922
 d_race_other |  -.0421649   .0047551    -8.87   0.000    -.0514848    -.032845
d_mar_married |   .0877741   .0047942    18.31   0.000     .0783776    .0971707
d_mar_unknown |   .1696926   .0666252     2.55   0.011     .0391087    .3002765
      d_st_GA |  -.0138776   .0055966    -2.48   0.013    -.0248467   -.0029085
      d_st_LA |   .0633345   .0078326     8.09   0.000     .0479828    .0786863
      d_st_MI |  -.0782374   .0052118   -15.01   0.000    -.0884525   -.0680223
      d_st_NC |  -.0071155   .0059438    -1.20   0.231    -.0187652    .0045342
      d_st_TX |  -.0706883   .0047428   -14.90   0.000    -.0799841   -.0613924
        _cons |   .1913341   .0135318    14.14   0.000     .1648121    .2178561
-------------------------------------------------------------------------------
(sum of wgt is   3.0505e+05)

Linear regression                               Number of obs     =    101,682
                                                F(15, 101681)     =      95.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0259
                                                Root MSE          =     .32108

                              (Std. Err. adjusted for 101,682 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .007512   .0035758     2.10   0.036     .0005034    .0145206
         t3_2 |   .0049408   .0037028     1.33   0.182    -.0023166    .0121982
          age |  -.0052156   .0010408    -5.01   0.000    -.0072556   -.0031756
         age2 |   .0112522   .0015913     7.07   0.000     .0081332    .0143712
     age_miss |   .1996816   .0738138     2.71   0.007     .0550075    .3443556
 d_race_black |  -.0415244   .0037769   -10.99   0.000    -.0489272   -.0341217
  d_race_hisp |   -.061585   .0036894   -16.69   0.000    -.0688161   -.0543538
 d_race_other |  -.0287234   .0055782    -5.15   0.000    -.0396565   -.0177903
d_mar_married |   .0711982   .0062851    11.33   0.000     .0588796    .0835169
d_mar_unknown |   .1519611   .0800212     1.90   0.058    -.0048795    .3088016
      d_st_GA |  -.0114588   .0062179    -1.84   0.065    -.0236457    .0007282
      d_st_LA |   .0648534   .0093693     6.92   0.000     .0464897     .083217
      d_st_MI |  -.0779449   .0057311   -13.60   0.000    -.0891777   -.0667121
      d_st_NC |  -.0005658   .0064613    -0.09   0.930    -.0132298    .0120983
      d_st_TX |  -.0565989   .0051926   -10.90   0.000    -.0667763   -.0464215
        _cons |    .225453    .016123    13.98   0.000     .1938521    .2570538
-------------------------------------------------------------------------------
(sum of wgt is   4.1560e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     20,780
                                                F(12, 20779)      =      28.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0406
                                                Root MSE          =     .43222

                               (Std. Err. adjusted for 20,780 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0046854   .0099029    -0.47   0.636    -.0240958    .0147249
         t3_2 |          0  (omitted)
          age |   .0499464   .0092055     5.43   0.000     .0319029      .06799
         age2 |  -.0346707   .0067343    -5.15   0.000    -.0478706   -.0214709
     age_miss |          0  (omitted)
 d_race_black |  -.0262309   .0130869    -2.00   0.045    -.0518823   -.0005795
  d_race_hisp |  -.0767538   .0142283    -5.39   0.000    -.1046423   -.0488653
 d_race_other |  -.1401055    .017376    -8.06   0.000    -.1741638   -.1060472
d_mar_married |   .1584371   .0197782     8.01   0.000     .1196702     .197204
d_mar_unknown |          0  (omitted)
      d_st_GA |  -.0072532   .0233056    -0.31   0.756     -.052934    .0384276
      d_st_LA |   .1410618   .0317107     4.45   0.000     .0789064    .2032172
      d_st_MI |  -.0963598   .0226493    -4.25   0.000    -.1407542   -.0519654
      d_st_NC |   .0561616   .0249184     2.25   0.024     .0073196    .1050036
      d_st_TX |  -.0716569     .02021    -3.55   0.000    -.1112701   -.0320436
        _cons |  -1.435668   .3109196    -4.62   0.000    -2.045095   -.8262414
-------------------------------------------------------------------------------
(sum of wgt is   2.0808e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     10,404
                                                F(11, 10403)      =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0427
                                                Root MSE          =     .40095

                               (Std. Err. adjusted for 10,404 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0097698   .0133393     0.73   0.464    -.0163778    .0359175
         t3_2 |          0  (omitted)
          age |   .0125659   .0145503     0.86   0.388    -.0159556    .0410874
         age2 |  -.0076759   .0108132    -0.71   0.478    -.0288718      .01352
     age_miss |          0  (omitted)
 d_race_black |  -.7415902   .0220921   -33.57   0.000    -.7848951   -.6982854
  d_race_hisp |  -.7292934   .0258895   -28.17   0.000    -.7800418    -.678545
 d_race_other |  -.7601667    .027314   -27.83   0.000    -.8137075   -.7066259
d_mar_married |   .0634803    .017867     3.55   0.000     .0284575    .0985032
d_mar_unknown |          0  (omitted)
      d_st_GA |  -.0782372   .0319349    -2.45   0.014    -.1408358   -.0156385
      d_st_LA |   .1478011   .0431906     3.42   0.001     .0631393    .2324629
      d_st_MI |  -.1041653   .0382067    -2.73   0.006    -.1790577   -.0292728
      d_st_NC |   .0483876   .0398001     1.22   0.224    -.0296283    .1264036
      d_st_TX |  -.1356142    .030206    -4.49   0.000    -.1948238   -.0764046
        _cons |    .534382   .4814294     1.11   0.267    -.4093122    1.478076
-------------------------------------------------------------------------------

. 
. * Plot everything
. set scheme s2mono

. 
. coefplot ( u55_1_agecat_17 \ u55_1_agecat_25 \ u55_1_agecat_35 \ u55_1_agecat_45 \ u55_0_agecat_55 
> \ u55_0_agecat_65 \ u55_0_agecat_75 \ u55_0_agecat_85 \ ///
>                         u55_1_race_black \ u55_1_race_hispanic \ u55_1_race_white \ u55_1_race_othe
> r \ u55_0_race_black \ u55_0_race_hispanic \ u55_0_race_white \ u55_0_race_other \ ///
>                         u55_1_gender_female \ u55_1_gender_not_female \ u55_0_gender_female \ u55_0
> _gender_not_female  ), /// 
>         keep(t3_1) xline(0) aseq swapnames xscale(range(-.2 .2)) xla(-.2(.05).2, labsize(vsmall))  
> t2title(Conditional Effects of Ballot Secrecy Interventions on Voting) ///
>         xtitle(Estimate, size(vsmall)) msize(*.6) ysize(11) xsize(15) ///
>         headings(u55_1_agecat_17="{bf:(A) By Age}" u55_1_race_black="{bf:(B) By Race, Under 55:}" u
> 55_0_race_black="{bf:(C) By Race, Over 55:}" ///
>                          u55_1_gender_female="{bf:(D) By Gender, Under 55:}" u55_0_gender_female="{
> bf:(E) By Gender, Over 55:}"  , labsize(vsmall)) ///
>         coeflabels(     u55_1_agecat_17="17-24" ///
>                                 u55_1_agecat_25="25-34" /// 
>                                 u55_1_agecat_35="35-44" /// 
>                                 u55_1_agecat_45="45-54" /// 
>                                 u55_0_agecat_55="55-64" /// 
>                                 u55_0_agecat_65="65-74" /// 
>                                 u55_0_agecat_75="75-84" /// 
>                                 u55_0_agecat_85="85-90" ///
>                                 u55_1_race_black="Black" ///
>                                 u55_1_race_hispanic="Hispanic" ///
>                                 u55_1_race_white="White" ///
>                                 u55_1_race_other="Other" ///
>                                 u55_0_race_black="Black" ///
>                                 u55_0_race_hispanic="Hispanic" ///
>                                 u55_0_race_white="White" ///
>                                 u55_0_race_other="Other" ///
>                                 u55_1_gender_female="Female" u55_1_gender_not_female="Not Female" /
> //
>                                 u55_0_gender_female="Female" u55_0_gender_not_female="Not Female"  
>      , labsize(vsmall)) 

.                                 
. graph export "FigureD1_SubgroupAnalysisCoefplot.pdf", replace
(file FigureD1_SubgroupAnalysisCoefplot.pdf written in PDF format)

. 
. /*-----------------------
> TABLES D6 AND D7: 
> Companion field experiment
>         D6: Ns by state and arm
>         D7: Standard GOTV mailer effects
>         
> NOTE: We are not authorized by the partner organization 
>         to provide a public replication data for these analyses.
>         Please email the corresponding author to request private 
>         replication files if interested.  Thank you.
> -----------------------*/
. 
. /*-----------------------
> TABLE D8: 
> Sensitivity to removing sample restriction
> ITT effects among original sample
> -----------------------*/
. local treat_vars = " t3_1 t3_2 "

. 
.         * loop over under/over 55 subgroups
.         forvalues u = 1(-1)0 {
  2.                 
.                 * define analysis sample condition
.                 local select = "under55==`u'"
  3.                 
.                 * define ipw to use
.                 local ipw = "ipw_t3_pooled_fs"
  4.                 
.                 * construct state-by-cov interactions
.                 foreach st in GA LA MI NC TX {
  5.                 foreach v in age age2 voted10 voted12 d_race_black d_race_hisp d_race_other d_ma
> r_married d_mar_unknown d_gend_female {
  6.                         gen Z_`st'_`v' = d_st_`st' * `v'
  7.                         quietly sum Z_`st'_`v' if `select'
  8.                         if (r(sd) == . | r(sd) == 0) {
  9.                                 drop Z_`st'_`v'
 10.                                 }
 11.                         }
 12.                 }
 13.                 
.                 if (`u' == 1) {                 // UNDER 55 ANALYSIS
 14.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' voted10 voted12 age age2 age_miss hhsize2 hhsize3 
> hhsize4 d_* [aweight=`ipw'] if `select', vce(cluster hhid)
 15.                         local adjr2 = e(r2_a)
 16.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 17.                         local c_turnout = r(mean)
 18.                         outreg2 using "TableD8_ITTEstimates_IncludeEverVoters.xls", se bracket d
> ec(3) label ctitle("Under 55,Experiment,Base Specification") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) replace
 19.                         
.                         * (2) all covs, YES state-by-cov interactions, with hhsize dummies, with ip
> w, with cluster SE   
.                         reg voted14 `treat_vars' voted10 voted12 age age2 age_miss hhsize2 hhsize3 
> hhsize4 d_* Z_* [aweight=`ipw'] if `select', vce(cluster hhid)
 20.                         local adjr2 = e(r2_a)
 21.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 22.                         local c_turnout = r(mean)
 23.                         outreg2 using "TableD8_ITTEstimates_IncludeEverVoters.xls", se bracket d
> ec(3) label ctitle("Under 55,Experiment,With State-by-,Covariate,Interactions") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", Y, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 24.                         
.                         * (3) all covs, NO state-by-cov interactions, with hhsize dummies, WITHOUT 
> ipw, WITHOUT cluster SE
.                         reg voted14 `treat_vars' voted10 voted12 age age2 age_miss hhsize2 hhsize3 
> hhsize4 d_* if `select'
 25.                         local adjr2 = e(r2_a)
 26.                         qui sum voted14 if t2==0 & e(sample)
 27.                         local c_turnout = r(mean)
 28.                         outreg2 using "TableD8_ITTEstimates_IncludeEverVoters.xls", se bracket d
> ec(3) label ctitle("Under 55,Experiment,Unweighted,and Without,HH-Level,Clustered-SE") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", N, "Household-Level Cluster
> ed SE?", N) append
 29.                         
. 
.                 }
 30.                 else {                                  // OVER 55 ANALYSIS
 31.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' voted10 voted12 age age2 age_miss hhsize2 hhsize3 
> hhsize4 d_* [aweight=`ipw'] if `select', vce(cluster hhid)
 32.                         local adjr2 = e(r2_a)
 33.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 34.                         local c_turnout = r(mean)
 35.                         outreg2 using "TableD8_ITTEstimates_IncludeEverVoters.xls", se bracket d
> ec(3) label ctitle("Over 55,Experiment,Base Specification") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 36.                 
.                         * (2) all covs, YES state-by-cov interactions, with hhsize dummies, with ip
> w, with cluster SE           
.                         reg voted14 `treat_vars' voted10 voted12 age age2 age_miss hhsize2 hhsize3 
> hhsize4 d_* Z_* [aweight=`ipw'] if `select', vce(cluster hhid)
 37.                         local adjr2 = e(r2_a)
 38.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 39.                         local c_turnout = r(mean)
 40.                         outreg2 using "TableD8_ITTEstimates_IncludeEverVoters.xls", se bracket d
> ec(3) label ctitle("Over 55,Experiment,With State-by-,Covariate,Interactions") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", Y, "Weighted?", Y, "Household-Level Cluster
> ed SE?", Y) append
 41.                 
.                         * (3) all covs, NO state-by-cov interactions, with hhsize dummies, WITHOUT 
> ipw, WITHOUT cluster SE
.                         reg voted14 `treat_vars' voted10 voted12 age age2 age_miss hhsize2 hhsize3 
> hhsize4 d_* if `select'
 42.                         local adjr2 = e(r2_a)
 43.                         qui sum voted14 if t2==0 & e(sample)
 44.                         local c_turnout = r(mean)
 45.                         outreg2 using "TableD8_ITTEstimates_IncludeEverVoters.xls", se bracket d
> ec(3) label ctitle("Over 55,Experiment,Unweighted,and Without,HH-Level,Clustered-SE") drop(Z*) ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("State-Covariate Interactions?", N, "Weighted?", N, "Household-Level Cluster
> ed SE?", N) append
 46.                         
.                         
.                 }
 47. 
.                 * drop interactions
.                 drop Z_*
 48.                 
.         }
(sum of wgt is   8.4711e+05)

Linear regression                               Number of obs     =    282,245
                                                F(21, 270646)     =     194.97
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0285
                                                Root MSE          =      .3376

                              (Std. Err. adjusted for 270,647 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0097737   .0023055     4.24   0.000     .0052549    .0142925
         t3_2 |   .0079991   .0023922     3.34   0.001     .0033105    .0126877
      voted10 |   .1345877   .0593555     2.27   0.023     .0182525    .2509229
      voted12 |    .210057   .0424991     4.94   0.000       .12676     .293354
          age |  -.0016321   .0005685    -2.87   0.004    -.0027464   -.0005179
         age2 |   .0059613   .0008525     6.99   0.000     .0042905    .0076321
     age_miss |   .1614802   .0485358     3.33   0.001     .0663514    .2566089
      hhsize2 |   .0084539   .0040219     2.10   0.036     .0005711    .0163366
      hhsize3 |   .0204454   .0185022     1.11   0.269    -.0158183    .0567092
      hhsize4 |   .0504406   .0892175     0.57   0.572    -.1244233    .2253045
 d_race_black |  -.0238856    .002299   -10.39   0.000    -.0283915   -.0193796
  d_race_hisp |  -.0483669   .0022583   -21.42   0.000    -.0527932   -.0439406
 d_race_other |  -.0271675    .003599    -7.55   0.000    -.0342215   -.0201136
d_mar_married |   .0846537   .0036201    23.38   0.000     .0775584    .0917489
d_mar_unknown |   .1580829   .0524638     3.01   0.003     .0552553    .2609105
d_gend_female |   .0135224   .0016837     8.03   0.000     .0102223    .0168224
      d_st_GA |  -.0101529   .0041005    -2.48   0.013    -.0181898    -.002116
      d_st_LA |   .0680341   .0059137    11.50   0.000     .0564434    .0796247
      d_st_MI |  -.0774849   .0037804   -20.50   0.000    -.0848945   -.0700754
      d_st_NC |   .0004925    .004333     0.11   0.910    -.0080001     .008985
      d_st_TX |  -.0641768   .0034417   -18.65   0.000    -.0709224   -.0574311
        _cons |   .1645893   .0092593    17.78   0.000     .1464413    .1827372
-------------------------------------------------------------------------------
TableD8_ITTEstimates_IncludeEverVoters.xls
dir : seeout
(sum of wgt is   8.4711e+05)
note: Z_GA_voted10 omitted because of collinearity

Linear regression                               Number of obs     =    282,245
                                                F(67, 270646)     =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0322
                                                Root MSE          =     .33699

                                   (Std. Err. adjusted for 270,647 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |   .0097583   .0022991     4.24   0.000     .0052522    .0142644
              t3_2 |   .0079261   .0023859     3.32   0.001     .0032498    .0126025
           voted10 |   .3825288    .154703     2.47   0.013     .0793151    .6857426
           voted12 |   .8370945   .0071228   117.52   0.000      .823134    .8510549
               age |  -.0098614   .0021936    -4.50   0.000    -.0141607    -.005562
              age2 |    .017072    .003306     5.16   0.000     .0105924    .0235517
          age_miss |   .1909155   .0493454     3.87   0.000     .0941999     .287631
           hhsize2 |   .0084662   .0040017     2.12   0.034      .000623    .0163094
           hhsize3 |   .0278509   .0182922     1.52   0.128    -.0080013    .0637032
           hhsize4 |   .0590299   .0900496     0.66   0.512    -.1174649    .2355247
      d_race_black |  -.0411096   .0072961    -5.63   0.000    -.0554099   -.0268094
       d_race_hisp |  -.0579649   .0115344    -5.03   0.000     -.080572   -.0353578
      d_race_other |   -.054445   .0157057    -3.47   0.001    -.0852278   -.0236622
     d_mar_married |   .1036955   .0161842     6.41   0.000     .0719749    .1354161
     d_mar_unknown |   .0341581   .0871875     0.39   0.695    -.1367269    .2050432
     d_gend_female |    .020385   .0063629     3.20   0.001      .007914    .0328561
           d_st_GA |  -.2493871   .0416284    -5.99   0.000    -.3309776   -.1677966
           d_st_LA |  -.1981371   .0619667    -3.20   0.001    -.3195901   -.0766841
           d_st_MI |  -.0091495   .0416272    -0.22   0.826    -.0907378    .0724387
           d_st_NC |  -.1004801   .0435582    -2.31   0.021    -.1858529   -.0151072
           d_st_TX |  -.2194482   .0341811    -6.42   0.000    -.2864422   -.1524542
          Z_GA_age |   .0136412     .00277     4.92   0.000      .008212    .0190703
         Z_GA_age2 |  -.0175911   .0041496    -4.24   0.000    -.0257243    -.009458
      Z_GA_voted10 |          0  (omitted)
      Z_GA_voted12 |  -.4467955   .1533037    -2.91   0.004    -.7472666   -.1463245
 Z_GA_d_race_black |   .0230395   .0094615     2.44   0.015     .0044951    .0415838
  Z_GA_d_race_hisp |   .0234767   .0146936     1.60   0.110    -.0053224    .0522759
 Z_GA_d_race_other |   .0019887   .0186648     0.11   0.915    -.0345938    .0385711
Z_GA_d_mar_married |   .0169801   .0194843     0.87   0.383    -.0212086    .0551689
Z_GA_d_mar_unknown |   .1957324   .0858578     2.28   0.023     .0274534    .3640114
Z_GA_d_gend_female |   .0041329   .0081942     0.50   0.614    -.0119276    .0201933
          Z_LA_age |   .0140076   .0040058     3.50   0.000     .0061564    .0218588
         Z_LA_age2 |  -.0173487   .0058909    -2.94   0.003    -.0288947   -.0058027
      Z_LA_voted10 |  -.6400475   .2954757    -2.17   0.030    -1.219172   -.0609232
      Z_LA_voted12 |   -.637853   .2512221    -2.54   0.011    -1.130241   -.1454646
 Z_LA_d_race_black |   .0308286    .013202     2.34   0.020     .0049529    .0567042
  Z_LA_d_race_hisp |   .0099126   .0237168     0.42   0.676    -.0365718    .0563969
 Z_LA_d_race_other |   .0514169   .0288254     1.78   0.074      -.00508    .1079139
Z_LA_d_mar_married |   .1182258   .0304824     3.88   0.000     .0584812    .1779704
Z_LA_d_mar_unknown |   .2316368   .0996796     2.32   0.020     .0362675     .427006
Z_LA_d_gend_female |     .00823   .0119788     0.69   0.492    -.0152482    .0317082
          Z_MI_age |  -.0048217   .0027792    -1.73   0.083    -.0102689    .0006255
         Z_MI_age2 |   .0057345   .0041956     1.37   0.172    -.0024887    .0139577
      Z_MI_voted10 |  -.3928608   .2399439    -1.64   0.102    -.8631442    .0774226
      Z_MI_voted12 |  -.6586566   .1194988    -5.51   0.000     -.892871   -.4244423
 Z_MI_d_race_black |    .043365   .0093484     4.64   0.000     .0250424    .0616875
  Z_MI_d_race_hisp |   .0603513   .0151332     3.99   0.000     .0306905     .090012
 Z_MI_d_race_other |   .1034187   .0181373     5.70   0.000     .0678701    .1389673
Z_MI_d_mar_married |  -.0241975   .0186998    -1.29   0.196    -.0608487    .0124537
Z_MI_d_gend_female |   .0018991   .0074741     0.25   0.799    -.0127501    .0165482
          Z_NC_age |   .0046624   .0029775     1.57   0.117    -.0011734    .0104982
         Z_NC_age2 |  -.0031542   .0045368    -0.70   0.487    -.0120462    .0057377
      Z_NC_voted10 |  -.0166344    .327678    -0.05   0.960    -.6588743    .6256056
      Z_NC_voted12 |  -.9853118   .0155115   -63.52   0.000    -1.015714   -.9549097
 Z_NC_d_race_black |   .0290414   .0100184     2.90   0.004     .0094057    .0486772
  Z_NC_d_race_hisp |  -.0065323   .0145025    -0.45   0.652    -.0349568    .0218921
 Z_NC_d_race_other |   .0554584   .0211646     2.62   0.009     .0139763    .0969406
Z_NC_d_mar_married |   .0036553   .0217066     0.17   0.866     -.038889    .0461997
Z_NC_d_gend_female |  -.0111864   .0085894    -1.30   0.193    -.0280215    .0056486
          Z_TX_age |   .0109609   .0023073     4.75   0.000     .0064387    .0154831
         Z_TX_age2 |  -.0153717   .0034767    -4.42   0.000    -.0221859   -.0085575
      Z_TX_voted10 |  -.2152449   .1668761    -1.29   0.197    -.5423176    .1118277
      Z_TX_voted12 |  -.6228519   .0471797   -13.20   0.000    -.7153228    -.530381
 Z_TX_d_race_black |   .0024166   .0080186     0.30   0.763    -.0132996    .0181328
  Z_TX_d_race_hisp |   .0011951    .011846     0.10   0.920    -.0220228    .0244129
 Z_TX_d_race_other |   .0078192   .0163835     0.48   0.633    -.0242921    .0399305
Z_TX_d_mar_married |  -.0390118   .0168129    -2.32   0.020    -.0719647    -.006059
Z_TX_d_mar_unknown |  -.2152334   .0821826    -2.62   0.009    -.3763091   -.0541577
Z_TX_d_gend_female |  -.0141447   .0067354    -2.10   0.036    -.0273458   -.0009436
             _cons |    .295421   .0325796     9.07   0.000     .2315659    .3592761
------------------------------------------------------------------------------------
TableD8_ITTEstimates_IncludeEverVoters.xls
dir : seeout

      Source |       SS           df       MS      Number of obs   =   282,245
-------------+----------------------------------   F(21, 282223)   =    401.53
       Model |  974.641047        21  46.4114784   Prob > F        =    0.0000
    Residual |  32621.2257   282,223  .115586702   R-squared       =    0.0290
-------------+----------------------------------   Adj R-squared   =    0.0289
       Total |  33595.8668   282,244  .119031288   Root MSE        =    .33998

-------------------------------------------------------------------------------
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0098188   .0022915     4.28   0.000     .0053275    .0143101
         t3_2 |    .008054   .0023718     3.40   0.001     .0034053    .0127028
      voted10 |   .1340107   .0341975     3.92   0.000     .0669846    .2010368
      voted12 |    .243134    .023818    10.21   0.000     .1964514    .2898166
          age |  -.0015057   .0003907    -3.85   0.000    -.0022714     -.00074
         age2 |   .0058542   .0005714    10.25   0.000     .0047343    .0069741
     age_miss |   .1462215   .0267435     5.47   0.000     .0938049    .1986381
      hhsize2 |   .0103055   .0025226     4.09   0.000     .0053614    .0152497
      hhsize3 |   .0062932   .0087104     0.72   0.470    -.0107789    .0233654
      hhsize4 |  -.0229045   .0260026    -0.88   0.378    -.0738689    .0280598
 d_race_black |   -.025429   .0016937   -15.01   0.000    -.0287487   -.0221094
  d_race_hisp |   -.047786   .0018185   -26.28   0.000    -.0513502   -.0442218
 d_race_other |  -.0218091   .0026732    -8.16   0.000    -.0270485   -.0165697
d_mar_married |   .0849873   .0023164    36.69   0.000     .0804473    .0895274
d_mar_unknown |   .1917706   .0285356     6.72   0.000     .1358416    .2476996
d_gend_female |    .014062    .001337    10.52   0.000     .0114416    .0166824
      d_st_GA |  -.0086275   .0028147    -3.07   0.002    -.0141442   -.0031107
      d_st_LA |   .0718259   .0037255    19.28   0.000      .064524    .0791279
      d_st_MI |  -.0778004   .0027551   -28.24   0.000    -.0832003   -.0724005
      d_st_NC |   -.003729   .0029025    -1.28   0.199    -.0094179    .0019599
      d_st_TX |  -.0660264   .0023926   -27.60   0.000    -.0707157    -.061337
        _cons |   .1624372   .0065745    24.71   0.000     .1495513    .1753231
-------------------------------------------------------------------------------
TableD8_ITTEstimates_IncludeEverVoters.xls
dir : seeout
(sum of wgt is   6.6050e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     33,071
                                                F(17, 32167)      =      42.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0549
                                                Root MSE          =     .42536

                               (Std. Err. adjusted for 32,168 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0039426   .0080374    -0.49   0.624    -.0196961     .011811
         t3_2 |          0  (omitted)
      voted10 |   .2559445   .0959496     2.67   0.008     .0678796    .4440094
      voted12 |    .329873   .0948527     3.48   0.001     .1439582    .5157877
          age |   .0430571   .0076576     5.62   0.000      .028048    .0580662
         age2 |  -.0296508   .0056256    -5.27   0.000    -.0406773   -.0186243
     age_miss |          0  (omitted)
      hhsize2 |   .1335595   .0265109     5.04   0.000     .0815971    .1855219
      hhsize3 |   -.115695   .0815023    -1.42   0.156    -.2754425    .0440525
      hhsize4 |          0  (omitted)
 d_race_black |   -.027945   .0116529    -2.40   0.016    -.0507851   -.0051049
  d_race_hisp |  -.0657554   .0124485    -5.28   0.000     -.090155   -.0413558
 d_race_other |  -.1085015   .0145881    -7.44   0.000    -.1370947   -.0799083
d_mar_married |   .1155543   .0131397     8.79   0.000     .0897999    .1413087
d_mar_unknown |          0  (omitted)
d_gend_female |   .0318704    .008891     3.58   0.000     .0144437    .0492971
      d_st_GA |  -.0304362   .0186146    -1.64   0.102    -.0669214    .0060491
      d_st_LA |   .1564811   .0250538     6.25   0.000     .1073748    .2055874
      d_st_MI |  -.0948674   .0195338    -4.86   0.000    -.1331545   -.0565803
      d_st_NC |   .0626853    .020929     3.00   0.003     .0216637     .103707
      d_st_TX |  -.0855154   .0167447    -5.11   0.000    -.1183356   -.0526952
        _cons |  -1.228188   .2581836    -4.76   0.000    -1.734238   -.7221386
-------------------------------------------------------------------------------
TableD8_ITTEstimates_IncludeEverVoters.xls
dir : seeout
(sum of wgt is   6.6050e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity
note: Z_GA_voted10 omitted because of collinearity
note: Z_MI_voted12 omitted because of collinearity

Linear regression                               Number of obs     =     33,071
                                                F(60, 32167)      =    1436.68
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0647
                                                Root MSE          =     .42343

                                    (Std. Err. adjusted for 32,168 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |  -.0029664   .0079722    -0.37   0.710    -.0185922    .0126595
              t3_2 |          0  (omitted)
           voted10 |    1.08152   .0592362    18.26   0.000     .9654146    1.197625
           voted12 |  -.1470238   .0473803    -3.10   0.002     -.239891   -.0541565
               age |   .0322716   .0333138     0.97   0.333    -.0330246    .0975679
              age2 |  -.0227283   .0248701    -0.91   0.361    -.0714747    .0260181
          age_miss |          0  (omitted)
           hhsize2 |    .129353   .0258196     5.01   0.000     .0787457    .1799604
           hhsize3 |  -.1262219    .087163    -1.45   0.148    -.2970648    .0446209
           hhsize4 |          0  (omitted)
      d_race_black |  -.0681281   .0402369    -1.69   0.090    -.1469939    .0107378
       d_race_hisp |  -.1474847   .0604888    -2.44   0.015    -.2660451   -.0289243
      d_race_other |  -.2092314   .0581074    -3.60   0.000    -.3231241   -.0953388
     d_mar_married |   .1535908   .0537971     2.86   0.004     .0481464    .2590352
     d_mar_unknown |          0  (omitted)
     d_gend_female |  -.0057318   .0383795    -0.15   0.881     -.080957    .0694934
           d_st_GA |   .0974802   1.276587     0.08   0.939    -2.404679     2.59964
           d_st_LA |  -1.064944    1.79488    -0.59   0.553    -4.582978    2.453089
           d_st_MI |  -1.335839    1.30498    -1.02   0.306    -3.893649     1.22197
           d_st_NC |  -1.313669   1.371263    -0.96   0.338    -4.001397    1.374059
           d_st_TX |  -.2874281   1.158723    -0.25   0.804    -2.558569    1.983712
          Z_GA_age |  -.0050771   .0382595    -0.13   0.894    -.0800672     .069913
         Z_GA_age2 |   .0031822   .0283787     0.11   0.911    -.0524411    .0588054
      Z_GA_voted10 |          0  (omitted)
      Z_GA_voted12 |  -.1963633    .076582    -2.56   0.010     -.346467   -.0462596
 Z_GA_d_race_black |   .0291291   .0501478     0.58   0.561    -.0691625    .1274207
  Z_GA_d_race_hisp |   .0984555    .073253     1.34   0.179    -.0451232    .2420341
 Z_GA_d_race_other |   .0555702   .0704778     0.79   0.430     -.082569    .1937093
Z_GA_d_mar_married |  -.0162001   .0623125    -0.26   0.795     -.138335    .1059347
Z_GA_d_gend_female |   .0763033   .0441644     1.73   0.084    -.0102606    .1628673
          Z_LA_age |   .0267191   .0542125     0.49   0.622    -.0795394    .1329776
         Z_LA_age2 |  -.0179159   .0405519    -0.44   0.659     -.097399    .0615673
      Z_LA_voted10 |  -1.124963   .1893472    -5.94   0.000    -1.496091   -.7538355
      Z_LA_voted12 |   .7769643    .187392     4.15   0.000      .409669     1.14426
 Z_LA_d_race_black |   .2310801   .0640567     3.61   0.000     .1055265    .3566336
  Z_LA_d_race_hisp |   .4525161   .1003459     4.51   0.000     .2558344    .6491978
 Z_LA_d_race_other |   .3794599   .1129341     3.36   0.001     .1581048     .600815
Z_LA_d_mar_married |   .1018122   .0741837     1.37   0.170    -.0435906     .247215
Z_LA_d_gend_female |   .0984456   .0581636     1.69   0.091    -.0155572    .2124484
          Z_MI_age |   .0345443   .0392263     0.88   0.379    -.0423407    .1114293
         Z_MI_age2 |   -.024304   .0291085    -0.83   0.404    -.0813578    .0327497
      Z_MI_voted10 |  -.2449037   .0798222    -3.07   0.002    -.4013582   -.0884491
      Z_MI_voted12 |          0  (omitted)
 Z_MI_d_race_black |   .0039876    .051592     0.08   0.938    -.0971346    .1051099
  Z_MI_d_race_hisp |   .1874411   .0833271     2.25   0.024     .0241168    .3507653
 Z_MI_d_race_other |   .1755552   .0717581     2.45   0.014     .0349067    .3162038
Z_MI_d_mar_married |  -.0721605   .0818753    -0.88   0.378    -.2326392    .0883182
Z_MI_d_gend_female |   .0173913   .0499903     0.35   0.728    -.0805915    .1153742
          Z_NC_age |   .0371094   .0410044     0.91   0.365    -.0432607    .1174795
         Z_NC_age2 |  -.0268689   .0303167    -0.89   0.375    -.0862908    .0325531
      Z_NC_voted10 |  -.5201593   .1300011    -4.00   0.000    -.7749663   -.2653523
      Z_NC_voted12 |   .3353147   .2556782     1.31   0.190    -.1658241    .8364536
 Z_NC_d_race_black |   .1401723    .055285     2.54   0.011     .0318116    .2485331
  Z_NC_d_race_hisp |    .049415   .0773154     0.64   0.523     -.102126     .200956
 Z_NC_d_race_other |   .0886893   .0747365     1.19   0.235     -.057797    .2351757
Z_NC_d_mar_married |   .0872353   .0700865     1.24   0.213    -.0501368    .2246074
Z_NC_d_gend_female |   .0656276   .0527228     1.24   0.213    -.0377111    .1689663
          Z_TX_age |   .0037396   .0349261     0.11   0.915    -.0647169    .0721962
         Z_TX_age2 |  -.0012307   .0260423    -0.05   0.962    -.0522746    .0498132
      Z_TX_voted10 |  -.9061819   .1273594    -7.12   0.000    -1.155811   -.6565526
      Z_TX_voted12 |   .5177763   .1124912     4.60   0.000     .2972893    .7382634
 Z_TX_d_race_black |  -.0088024   .0436507    -0.20   0.840    -.0943594    .0767546
  Z_TX_d_race_hisp |    .054662   .0623713     0.88   0.381     -.067588     .176912
 Z_TX_d_race_other |   .0767815   .0611185     1.26   0.209     -.043013    .1965761
Z_TX_d_mar_married |  -.0681429   .0559204    -1.22   0.223     -.177749    .0414632
Z_TX_d_gend_female |   .0266851   .0399549     0.67   0.504     -.051628    .1049982
             _cons |  -.7762669   1.104006    -0.70   0.482     -2.94016    1.387626
------------------------------------------------------------------------------------
TableD8_ITTEstimates_IncludeEverVoters.xls
dir : seeout
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =    33,071
-------------+----------------------------------   F(17, 33053)    =    112.35
       Model |    344.4233        17  20.2601941   Prob > F        =    0.0000
    Residual |  5960.66478    33,053  .180336574   R-squared       =    0.0546
-------------+----------------------------------   Adj R-squared   =    0.0541
       Total |  6305.08808    33,070  .190658847   Root MSE        =    .42466

-------------------------------------------------------------------------------
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0038949   .0077949    -0.50   0.617    -.0191732    .0113834
         t3_2 |          0  (omitted)
      voted10 |   .2924366   .0733876     3.98   0.000     .1485942     .436279
      voted12 |   .1852341   .0605339     3.06   0.002     .0665855    .3038827
          age |   .0393058   .0044311     8.87   0.000     .0306206     .047991
         age2 |  -.0271387   .0032484    -8.35   0.000    -.0335056   -.0207717
     age_miss |          0  (omitted)
      hhsize2 |   .1088279   .0112492     9.67   0.000      .086779    .1308767
      hhsize3 |   -.116939   .0867734    -1.35   0.178     -.287018      .05314
      hhsize4 |          0  (omitted)
 d_race_black |  -.0308931   .0068261    -4.53   0.000    -.0442725   -.0175137
  d_race_hisp |  -.0686786     .00745    -9.22   0.000    -.0832809   -.0540763
 d_race_other |  -.1133528   .0088996   -12.74   0.000    -.1307962   -.0959093
d_mar_married |   .1165548   .0073705    15.81   0.000     .1021083    .1310013
d_mar_unknown |          0  (omitted)
d_gend_female |   .0264077   .0056781     4.65   0.000     .0152785    .0375369
      d_st_GA |  -.0206564   .0104364    -1.98   0.048    -.0411121   -.0002008
      d_st_LA |   .1447225   .0132728    10.90   0.000     .1187074    .1707376
      d_st_MI |  -.1062286   .0112368    -9.45   0.000    -.1282531   -.0842041
      d_st_NC |   .0678064   .0113841     5.96   0.000     .0454931    .0901196
      d_st_TX |  -.0965648   .0093913   -10.28   0.000    -.1149721   -.0781576
        _cons |  -1.079659   .1499054    -7.20   0.000    -1.373479   -.7858387
-------------------------------------------------------------------------------
TableD8_ITTEstimates_IncludeEverVoters.xls
dir : seeout

. 
. /*-----------------------
> APPENDIX E - All tables
> Balance Tables and Randomization Checks
> -----------------------*/
. 
. * Table E1: Under 55 Experiment, Registered Never-Voters
. 
. local select = "if never_voted == 1 & under55 == 1"

. local covs = "d_race_black d_race_hisp d_race_other d_gend_female d_mar_married d_mar_unknown d_st_
> GA d_st_LA d_st_MI d_st_NC d_st_TX age age2 age_miss"

. 
. mlogit t3 `covs' [pweight=ipw_t3_pooled_nv] `select', vce(cluster hhid) baseoutcome(0)

Iteration 0:   log pseudolikelihood = -929646.87  
Iteration 1:   log pseudolikelihood = -929591.16  
Iteration 2:   log pseudolikelihood = -929591.15  

Multinomial logistic regression                 Number of obs     =    281,943
                                                Wald chi2(28)     =      17.72
                                                Prob > chi2       =     0.9330
Log pseudolikelihood = -929591.15               Pseudo R2         =     0.0001

                                    (Std. Err. adjusted for 270,358 clusters in hhid)
-------------------------------------------------------------------------------------
                    |               Robust
                 t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
0__control          |  (base outcome)
--------------------+----------------------------------------------------------------
1__ballot_secrecy   |
       d_race_black |   .0123132   .0181547     0.68   0.498    -.0232693    .0478957
        d_race_hisp |   .0252836    .019737     1.28   0.200    -.0134002    .0639674
       d_race_other |   .0011016   .0297683     0.04   0.970    -.0572431    .0594463
      d_gend_female |  -.0088739   .0139181    -0.64   0.524    -.0361528     .018405
      d_mar_married |   .0108672   .0261408     0.42   0.678    -.0403677    .0621022
      d_mar_unknown |  -.3655192    .284029    -1.29   0.198    -.9222058    .1911675
            d_st_GA |  -.0060222   .0308246    -0.20   0.845    -.0664373    .0543929
            d_st_LA |   .0028732   .0405728     0.07   0.944     -.076648    .0823943
            d_st_MI |   .0014418   .0301843     0.05   0.962    -.0577184    .0606019
            d_st_NC |   .0013463   .0317503     0.04   0.966     -.060883    .0635757
            d_st_TX |  -.0093059   .0262214    -0.35   0.723     -.060699    .0420872
                age |   .0026052   .0041646     0.63   0.532    -.0055574    .0107677
               age2 |  -.0016813   .0061216    -0.27   0.784    -.0136794    .0103168
           age_miss |   .1667853    .271991     0.61   0.540    -.3663072    .6998779
              _cons |   -.058717   .0667138    -0.88   0.379    -.1894737    .0720397
--------------------+----------------------------------------------------------------
2__personalized_url |
       d_race_black |  -.0047578    .018806    -0.25   0.800    -.0416168    .0321012
        d_race_hisp |   .0136836   .0204315     0.67   0.503    -.0263614    .0537285
       d_race_other |  -.0221835    .030844    -0.72   0.472    -.0826367    .0382697
      d_gend_female |  -.0086363   .0144077    -0.60   0.549    -.0368749    .0196023
      d_mar_married |   .0135605   .0270219     0.50   0.616    -.0394013    .0665224
      d_mar_unknown |  -.1279372   .3003219    -0.43   0.670    -.7165574     .460683
            d_st_GA |   -.001924   .0318928    -0.06   0.952    -.0644328    .0605847
            d_st_LA |   .0080966   .0419974     0.19   0.847    -.0742167    .0904099
            d_st_MI |  -.0009092   .0312373    -0.03   0.977    -.0621332    .0603149
            d_st_NC |   .0082842   .0328602     0.25   0.801    -.0561207    .0726891
            d_st_TX |  -.0039418   .0271307    -0.15   0.884     -.057117    .0492334
                age |   .0031315   .0043298     0.72   0.470    -.0053548    .0116178
               age2 |  -.0016427   .0063646    -0.26   0.796     -.014117    .0108317
           age_miss |   -.017872   .2892323    -0.06   0.951     -.584757    .5490129
              _cons |  -.0683357   .0692912    -0.99   0.324    -.2041439    .0674726
-------------------------------------------------------------------------------------

. testparm `covs'

 ( 1)  [0__control]o.d_race_black = 0
 ( 2)  [1__ballot_secrecy]d_race_black = 0
 ( 3)  [2__personalized_url]d_race_black = 0
 ( 4)  [0__control]o.d_race_hisp = 0
 ( 5)  [1__ballot_secrecy]d_race_hisp = 0
 ( 6)  [2__personalized_url]d_race_hisp = 0
 ( 7)  [0__control]o.d_race_other = 0
 ( 8)  [1__ballot_secrecy]d_race_other = 0
 ( 9)  [2__personalized_url]d_race_other = 0
 (10)  [0__control]o.d_gend_female = 0
 (11)  [1__ballot_secrecy]d_gend_female = 0
 (12)  [2__personalized_url]d_gend_female = 0
 (13)  [0__control]o.d_mar_married = 0
 (14)  [1__ballot_secrecy]d_mar_married = 0
 (15)  [2__personalized_url]d_mar_married = 0
 (16)  [0__control]o.d_mar_unknown = 0
 (17)  [1__ballot_secrecy]d_mar_unknown = 0
 (18)  [2__personalized_url]d_mar_unknown = 0
 (19)  [0__control]o.d_st_GA = 0
 (20)  [1__ballot_secrecy]d_st_GA = 0
 (21)  [2__personalized_url]d_st_GA = 0
 (22)  [0__control]o.d_st_LA = 0
 (23)  [1__ballot_secrecy]d_st_LA = 0
 (24)  [2__personalized_url]d_st_LA = 0
 (25)  [0__control]o.d_st_MI = 0
 (26)  [1__ballot_secrecy]d_st_MI = 0
 (27)  [2__personalized_url]d_st_MI = 0
 (28)  [0__control]o.d_st_NC = 0
 (29)  [1__ballot_secrecy]d_st_NC = 0
 (30)  [2__personalized_url]d_st_NC = 0
 (31)  [0__control]o.d_st_TX = 0
 (32)  [1__ballot_secrecy]d_st_TX = 0
 (33)  [2__personalized_url]d_st_TX = 0
 (34)  [0__control]o.age = 0
 (35)  [1__ballot_secrecy]age = 0
 (36)  [2__personalized_url]age = 0
 (37)  [0__control]o.age2 = 0
 (38)  [1__ballot_secrecy]age2 = 0
 (39)  [2__personalized_url]age2 = 0
 (40)  [0__control]o.age_miss = 0
 (41)  [1__ballot_secrecy]age_miss = 0
 (42)  [2__personalized_url]age_miss = 0
       Constraint 1 dropped
       Constraint 4 dropped
       Constraint 7 dropped
       Constraint 10 dropped
       Constraint 13 dropped
       Constraint 16 dropped
       Constraint 19 dropped
       Constraint 22 dropped
       Constraint 25 dropped
       Constraint 28 dropped
       Constraint 31 dropped
       Constraint 34 dropped
       Constraint 37 dropped
       Constraint 40 dropped

           chi2( 28) =   17.72
         Prob > chi2 =    0.9330

. local ftest = round(r(p), 0.001)

. forval i = 0(1)2 {
  2. local clabel : label (t3) `i'
  3. if `i' == 0 {
  4.         outsum `covs' [aweight=ipw_t3_pooled_nv] `select' & t3 == `i' using "TableE1_BalanceTabl
> e_Under55_NeverVoters.out" , ///
>                 replace ctitle("`clabel'") bracket addnote("F-test p-value: 0`ftest'") 
  5. }
  6. else {
  7.         outsum `covs' [aweight=ipw_t3_pooled_nv] `select' & t3 == `i' using "TableE1_BalanceTabl
> e_Under55_NeverVoters.out" , ///
>                 append ctitle("`clabel'") bracket 
  8. }
  9. }

. 
. * Table E2: Over 55 Experiment, Registered Never-Voters
. 
. local select = "if never_voted == 1 & under55 == 0"

. local covs = "d_race_black d_race_hisp d_race_other d_gend_female d_mar_married d_mar_unknown d_st_
> GA d_st_LA d_st_MI d_st_NC d_st_TX age age2 age_miss"

. 
. logit t3 `covs' [pweight=ipw_t3_pooled_nv] `select', vce(cluster hhid) 

note: d_mar_unknown omitted because of collinearity
note: age_miss omitted because of collinearity
Iteration 0:   log pseudolikelihood = -45655.311  
Iteration 1:   log pseudolikelihood = -45633.586  
Iteration 2:   log pseudolikelihood = -45633.586  

Logistic regression                             Number of obs     =     32,979
                                                Wald chi2(12)     =       8.05
                                                Prob > chi2       =     0.7811
Log pseudolikelihood = -45633.586               Pseudo R2         =     0.0005

                               (Std. Err. adjusted for 32,078 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
           t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 d_race_black |  -.0380371   .0534413    -0.71   0.477    -.1427802     .066706
  d_race_hisp |  -.0122141   .0586129    -0.21   0.835    -.1270931     .102665
 d_race_other |  -.0192177   .0716794    -0.27   0.789    -.1597066    .1212713
d_gend_female |  -.1015731    .043488    -2.34   0.020    -.1868081   -.0163381
d_mar_married |   .0054419   .0595499     0.09   0.927    -.1112738    .1221575
d_mar_unknown |          0  (omitted)
      d_st_GA |   .0107437   .0833079     0.13   0.897    -.1525368    .1740242
      d_st_LA |  -.0213175   .1056481    -0.20   0.840     -.228384     .185749
      d_st_MI |   .0032014   .0894449     0.04   0.971    -.1721074    .1785102
      d_st_NC |   .0014064   .0910658     0.02   0.988    -.1770794    .1798922
      d_st_TX |  -.0110478   .0746829    -0.15   0.882    -.1574237     .135328
          age |   .0206943   .0350617     0.59   0.555    -.0480254    .0894139
         age2 |  -.0129703   .0257165    -0.50   0.614    -.0633736    .0374331
     age_miss |          0  (omitted)
        _cons |  -.6935514   1.184563    -0.59   0.558    -3.015252     1.62815
-------------------------------------------------------------------------------

. testparm `covs'

 ( 1)  [t3]d_race_black = 0
 ( 2)  [t3]d_race_hisp = 0
 ( 3)  [t3]d_race_other = 0
 ( 4)  [t3]d_gend_female = 0
 ( 5)  [t3]d_mar_married = 0
 ( 6)  [t3]d_st_GA = 0
 ( 7)  [t3]d_st_LA = 0
 ( 8)  [t3]d_st_MI = 0
 ( 9)  [t3]d_st_NC = 0
 (10)  [t3]d_st_TX = 0
 (11)  [t3]age = 0
 (12)  [t3]age2 = 0

           chi2( 12) =    8.05
         Prob > chi2 =    0.7811

. local ftest = round(r(p), 0.001)

. forval i = 0(1)1 {
  2. local clabel : label (t3) `i'
  3. if `i' == 0 {
  4.         outsum `covs' [aweight=ipw_t3_pooled_nv] `select' & t3 == `i' using "TableE2_BalanceTabl
> e_Over55_NeverVoters.out" , ///
>                 replace ctitle("`clabel'") bracket addnote("F-test p-value: 0`ftest'") 
  5. }
  6. else {
  7.         outsum `covs' [aweight=ipw_t3_pooled_nv] `select' & t3 == `i' using "TableE2_BalanceTabl
> e_Over55_NeverVoters.out" , ///
>                 append ctitle("`clabel'") bracket 
  8. }
  9. }

. 
. * Tables E3 through E14 : By State, Over/Under 55 Balance Tables, Registered Never-Voters
. 
. levelsof state, local(states)
`"AR"' `"GA"' `"LA"' `"MI"' `"NC"' `"TX"'

. 
. foreach s in `states' {
  2.         local covs = "d_race_black d_race_hisp d_race_other d_gend_female d_mar_married d_mar_un
> known age age2 age_miss"
  3. 
.         *======= Under 55 =======*
.         local select = "if never_voted == 1 & under55 == 1"
  4.         
.         * Randomization check -- Note: Some factor levels (for covariates) perfectly predict treatm
> ent in NC (due to small sample size); omit as predictor in randomization check
.         if ("`s'" != "NC") {
  5.                 mlogit t3 `covs' [pweight=ipw_t3_pooled_nv] `select' & state == "`s'", vce(clust
> er hhid) baseoutcome(0)
  6.                 testparm `covs'
  7.                 local ftest = round(r(p), 0.001)
  8.         }
  9.         else if ("`s'" == "NC") {
 10.                 local covsNC = "d_race_black d_race_hisp d_race_other d_mar_married d_mar_unknow
> n age age2 d_gend_female"
 11.                 mlogit t3 `covsNC' [pweight=ipw_t3_pooled_nv] `select' & state == "`s'", vce(clu
> ster hhid) baseoutcome(0)
 12.                 testparm `covsNC'
 13.                 local ftest = round(r(p), 0.001)
 14.         }
 15.         
.         forval i = 0(1)2 {
 16.                 if `i' == 0 {
 17.                         local clabel = "Control"
 18.                 }
 19.                 else if `i' == 1 {
 20.                         local clabel = "Ballot Secrecy"
 21.                 }
 22.                 else if `i' == 2 {
 23.                         local clabel = "Personalized URL"
 24.                 }
 25. 
.                 if `i' == 0 {
 26.                         outsum `covs' [aweight=ipw_t3_pooled_st_nv] `select' & state == "`s'" & 
> t3 == `i' using "TablesE3toE14_BalanceTables_Under55_NeverVoters_`s'.out" , ///
>                                 replace ctitle("`clabel'") bracket addnote("F-test p-value: 0`ftest
> '") 
 27.                 }
 28.                 else {
 29.                         outsum `covs' [aweight=ipw_t3_pooled_st_nv] `select' & state == "`s'" & 
> t3 == `i' using "TablesE3toE14_BalanceTables_Under55_NeverVoters_`s'.out" , ///
>                                 append ctitle("`clabel'") bracket 
 30.                 }
 31.         }
 32.         
.         *======= Over 55 =======*
.         local select = "if never_voted == 1 & under55 == 0"
 33.         
.         * Randomization check
.         logit t3 `covs' [pweight=ipw_t3_pooled_st_nv] `select' & state == "`s'", vce(cluster hhid) 
 34.         testparm `covs'
 35.         local ftest = round(r(p), 0.001)
 36. 
.         forval i = 0(1)1 {
 37.                 if `i' == 0 {
 38.                         local clabel = "Control"
 39.                 }
 40.                 else if `i' == 1 {
 41.                         local clabel = "Ballot Secrecy"
 42.                 }
 43. 
.                 if `i' == 0 {
 44.                         outsum `covs' [aweight=ipw_t3_pooled_st_nv] `select' & state == "`s'" & 
> t3 == `i' using "TablesE3toE14_BalanceTables_Over55_NeverVoters_`s'.out" , ///
>                                 replace ctitle("`clabel'") bracket addnote("F-test p-value: 0`ftest
> '") 
 45.                 }
 46.                 else {
 47.                         outsum `covs' [aweight=ipw_t3_pooled_st_nv] `select' & state == "`s'" & 
> t3 == `i' using "TablesE3toE14_BalanceTables_Over55_NeverVoters_`s'.out" , ///
>                                 append ctitle("`clabel'") bracket 
 48.                 }
 49.         }
 50. 
. }

Iteration 0:   log pseudolikelihood =  -83198.81  
Iteration 1:   log pseudolikelihood = -83145.326  
Iteration 2:   log pseudolikelihood = -83145.214  
Iteration 3:   log pseudolikelihood = -83145.214  

Multinomial logistic regression                 Number of obs     =     25,223
                                                Wald chi2(18)     =      20.06
                                                Prob > chi2       =     0.3293
Log pseudolikelihood = -83145.214               Pseudo R2         =     0.0006

                                     (Std. Err. adjusted for 24,256 clusters in hhid)
-------------------------------------------------------------------------------------
                    |               Robust
                 t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
0__control          |  (base outcome)
--------------------+----------------------------------------------------------------
1__ballot_secrecy   |
       d_race_black |  -.0247884   .0535915    -0.46   0.644    -.1298259     .080249
        d_race_hisp |   .0347928   .0904465     0.38   0.700     -.142479    .2120646
       d_race_other |  -.2712024   .1283277    -2.11   0.035      -.52272   -.0196848
      d_gend_female |  -.0865786   .0467969    -1.85   0.064    -.1782988    .0051416
      d_mar_married |   .0700161   .1077688     0.65   0.516    -.1412067     .281239
      d_mar_unknown |  -.3606241   .8898349    -0.41   0.685    -2.104669     1.38342
                age |   .0114492   .0151758     0.75   0.451    -.0182947    .0411931
               age2 |  -.0113289   .0226746    -0.50   0.617    -.0557704    .0331125
           age_miss |   .5574297   .7414577     0.75   0.452    -.8958007     2.01066
              _cons |  -.1548249   .2242191    -0.69   0.490    -.5942863    .2846364
--------------------+----------------------------------------------------------------
2__personalized_url |
       d_race_black |  -.0444043   .0555272    -0.80   0.424    -.1532356     .064427
        d_race_hisp |  -.0735571   .0941324    -0.78   0.435    -.2580531    .1109389
       d_race_other |   -.251194   .1328014    -1.89   0.059      -.51148    .0090921
      d_gend_female |   -.067895   .0484305    -1.40   0.161    -.1628171    .0270271
      d_mar_married |   -.027535   .1120236    -0.25   0.806    -.2470972    .1920271
      d_mar_unknown |  -.9891241   .9013908    -1.10   0.272    -2.755818    .7775694
                age |   .0097372   .0155993     0.62   0.532    -.0208369    .0403114
               age2 |  -.0079979   .0232689    -0.34   0.731    -.0536041    .0376083
           age_miss |   .8285021   .7417557     1.12   0.264    -.6253123    2.282316
              _cons |  -.1291654    .230861    -0.56   0.576    -.5816446    .3233138
-------------------------------------------------------------------------------------

 ( 1)  [0__control]o.d_race_black = 0
 ( 2)  [1__ballot_secrecy]d_race_black = 0
 ( 3)  [2__personalized_url]d_race_black = 0
 ( 4)  [0__control]o.d_race_hisp = 0
 ( 5)  [1__ballot_secrecy]d_race_hisp = 0
 ( 6)  [2__personalized_url]d_race_hisp = 0
 ( 7)  [0__control]o.d_race_other = 0
 ( 8)  [1__ballot_secrecy]d_race_other = 0
 ( 9)  [2__personalized_url]d_race_other = 0
 (10)  [0__control]o.d_gend_female = 0
 (11)  [1__ballot_secrecy]d_gend_female = 0
 (12)  [2__personalized_url]d_gend_female = 0
 (13)  [0__control]o.d_mar_married = 0
 (14)  [1__ballot_secrecy]d_mar_married = 0
 (15)  [2__personalized_url]d_mar_married = 0
 (16)  [0__control]o.d_mar_unknown = 0
 (17)  [1__ballot_secrecy]d_mar_unknown = 0
 (18)  [2__personalized_url]d_mar_unknown = 0
 (19)  [0__control]o.age = 0
 (20)  [1__ballot_secrecy]age = 0
 (21)  [2__personalized_url]age = 0
 (22)  [0__control]o.age2 = 0
 (23)  [1__ballot_secrecy]age2 = 0
 (24)  [2__personalized_url]age2 = 0
 (25)  [0__control]o.age_miss = 0
 (26)  [1__ballot_secrecy]age_miss = 0
 (27)  [2__personalized_url]age_miss = 0
       Constraint 1 dropped
       Constraint 4 dropped
       Constraint 7 dropped
       Constraint 10 dropped
       Constraint 13 dropped
       Constraint 16 dropped
       Constraint 19 dropped
       Constraint 22 dropped
       Constraint 25 dropped

           chi2( 18) =   20.06
         Prob > chi2 =    0.3293

note: d_mar_unknown omitted because of collinearity
note: age_miss omitted because of collinearity
Iteration 0:   log pseudolikelihood = -3465.2063  
Iteration 1:   log pseudolikelihood = -3456.3016  
Iteration 2:   log pseudolikelihood = -3456.3012  
Iteration 3:   log pseudolikelihood = -3456.3012  

Logistic regression                             Number of obs     =      2,505
                                                Wald chi2(7)      =       3.00
                                                Prob > chi2       =     0.8851
Log pseudolikelihood = -3456.3012               Pseudo R2         =     0.0026

                                (Std. Err. adjusted for 2,463 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
           t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 d_race_black |   -.011302   .1756139    -0.06   0.949    -.3554989     .332895
  d_race_hisp |   .3051477     .32894     0.93   0.354    -.3395628    .9498583
 d_race_other |   .1862045   .3526039     0.53   0.597    -.5048864    .8772954
d_gend_female |  -.1008428   .1792907    -0.56   0.574    -.4522461    .2505605
d_mar_married |  -.1625865   .2252511    -0.72   0.470    -.6040704    .2788975
d_mar_unknown |          0  (omitted)
          age |   .1054872   .1291854     0.82   0.414    -.1477115    .3586859
         age2 |  -.0749142   .0950792    -0.79   0.431    -.2612659    .1114376
     age_miss |          0  (omitted)
        _cons |   -3.56842   4.346753    -0.82   0.412     -12.0879    4.951061
-------------------------------------------------------------------------------

 ( 1)  [t3]d_race_black = 0
 ( 2)  [t3]d_race_hisp = 0
 ( 3)  [t3]d_race_other = 0
 ( 4)  [t3]d_gend_female = 0
 ( 5)  [t3]d_mar_married = 0
 ( 6)  [t3]age = 0
 ( 7)  [t3]age2 = 0

           chi2(  7) =    3.00
         Prob > chi2 =    0.8851

Iteration 0:   log pseudolikelihood = -120381.69  
Iteration 1:   log pseudolikelihood = -120311.49  
Iteration 2:   log pseudolikelihood = -120311.46  
Iteration 3:   log pseudolikelihood = -120311.46  

Multinomial logistic regression                 Number of obs     =     36,503
                                                Wald chi2(18)     =      24.41
                                                Prob > chi2       =     0.1421
Log pseudolikelihood = -120311.46               Pseudo R2         =     0.0006

                                     (Std. Err. adjusted for 35,197 clusters in hhid)
-------------------------------------------------------------------------------------
                    |               Robust
                 t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
0__control          |  (base outcome)
--------------------+----------------------------------------------------------------
1__ballot_secrecy   |
       d_race_black |   .0250692   .0443844     0.56   0.572    -.0619226    .1120611
        d_race_hisp |   .1530285    .073333     2.09   0.037     .0092985    .2967585
       d_race_other |   .1423507   .0830911     1.71   0.087     -.020505    .3052063
      d_gend_female |   .0027461   .0389793     0.07   0.944    -.0736519    .0791441
      d_mar_married |  -.0270884   .0698367    -0.39   0.698    -.1639658    .1097889
      d_mar_unknown |  -.3358981   .3740607    -0.90   0.369    -1.069044    .3972473
                age |   -.020439   .0115068    -1.78   0.076     -.042992     .002114
               age2 |   .0260704   .0167319     1.56   0.119    -.0067234    .0588642
           age_miss |    .270444   .4032395     0.67   0.502     -.519891    1.060779
              _cons |    .305906    .181077     1.69   0.091    -.0489984    .6608104
--------------------+----------------------------------------------------------------
2__personalized_url |
       d_race_black |   .0313372   .0460419     0.68   0.496    -.0589033    .1215777
        d_race_hisp |   .2346465   .0753958     3.11   0.002     .0868735    .3824196
       d_race_other |   .1679615   .0856168     1.96   0.050     .0001557    .3357674
      d_gend_female |   .0127184   .0403249     0.32   0.752     -.066317    .0917537
      d_mar_married |   .0393545   .0719401     0.55   0.584    -.1016456    .1803545
      d_mar_unknown |  -.0094591    .392499    -0.02   0.981    -.7787431    .7598248
                age |  -.0114213   .0120278    -0.95   0.342    -.0349954    .0121528
               age2 |   .0126542   .0175032     0.72   0.470    -.0216515      .04696
           age_miss |   .0359108   .4258725     0.08   0.933     -.798784    .8706056
              _cons |   .1442201   .1890834     0.76   0.446    -.2263766    .5148168
-------------------------------------------------------------------------------------

 ( 1)  [0__control]o.d_race_black = 0
 ( 2)  [1__ballot_secrecy]d_race_black = 0
 ( 3)  [2__personalized_url]d_race_black = 0
 ( 4)  [0__control]o.d_race_hisp = 0
 ( 5)  [1__ballot_secrecy]d_race_hisp = 0
 ( 6)  [2__personalized_url]d_race_hisp = 0
 ( 7)  [0__control]o.d_race_other = 0
 ( 8)  [1__ballot_secrecy]d_race_other = 0
 ( 9)  [2__personalized_url]d_race_other = 0
 (10)  [0__control]o.d_gend_female = 0
 (11)  [1__ballot_secrecy]d_gend_female = 0
 (12)  [2__personalized_url]d_gend_female = 0
 (13)  [0__control]o.d_mar_married = 0
 (14)  [1__ballot_secrecy]d_mar_married = 0
 (15)  [2__personalized_url]d_mar_married = 0
 (16)  [0__control]o.d_mar_unknown = 0
 (17)  [1__ballot_secrecy]d_mar_unknown = 0
 (18)  [2__personalized_url]d_mar_unknown = 0
 (19)  [0__control]o.age = 0
 (20)  [1__ballot_secrecy]age = 0
 (21)  [2__personalized_url]age = 0
 (22)  [0__control]o.age2 = 0
 (23)  [1__ballot_secrecy]age2 = 0
 (24)  [2__personalized_url]age2 = 0
 (25)  [0__control]o.age_miss = 0
 (26)  [1__ballot_secrecy]age_miss = 0
 (27)  [2__personalized_url]age_miss = 0
       Constraint 1 dropped
       Constraint 4 dropped
       Constraint 7 dropped
       Constraint 10 dropped
       Constraint 13 dropped
       Constraint 16 dropped
       Constraint 19 dropped
       Constraint 22 dropped
       Constraint 25 dropped

           chi2( 18) =   24.41
         Prob > chi2 =    0.1421

note: d_mar_unknown omitted because of collinearity
note: age_miss omitted because of collinearity
Iteration 0:   log pseudolikelihood = -7005.4163  
Iteration 1:   log pseudolikelihood = -6993.0568  
Iteration 2:   log pseudolikelihood = -6993.0564  

Logistic regression                             Number of obs     =      5,091
                                                Wald chi2(7)      =       4.13
                                                Prob > chi2       =     0.7643
Log pseudolikelihood = -6993.0564               Pseudo R2         =     0.0018

                                (Std. Err. adjusted for 4,937 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
           t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 d_race_black |  -.0853898    .133364    -0.64   0.522    -.3467785    .1759989
  d_race_hisp |   .1536701   .2011285     0.76   0.445    -.2405345    .5478747
 d_race_other |  -.1357255   .1874749    -0.72   0.469    -.5031696    .2317185
d_gend_female |  -.0848721   .1034366    -0.82   0.412    -.2876041    .1178599
d_mar_married |    .049262   .1444461     0.34   0.733    -.2338471    .3323711
d_mar_unknown |          0  (omitted)
          age |  -.0851431   .0928361    -0.92   0.359    -.2670985    .0968122
         age2 |   .0652528   .0683909     0.95   0.340     -.068791    .1992965
     age_miss |          0  (omitted)
        _cons |   2.853518   3.119274     0.91   0.360    -3.260147    8.967184
-------------------------------------------------------------------------------

 ( 1)  [t3]d_race_black = 0
 ( 2)  [t3]d_race_hisp = 0
 ( 3)  [t3]d_race_other = 0
 ( 4)  [t3]d_gend_female = 0
 ( 5)  [t3]d_mar_married = 0
 ( 6)  [t3]age = 0
 ( 7)  [t3]age2 = 0

           chi2(  7) =    4.13
         Prob > chi2 =    0.7643

Iteration 0:   log pseudolikelihood = -41862.701  
Iteration 1:   log pseudolikelihood =  -41835.89  
Iteration 2:   log pseudolikelihood = -41835.802  
Iteration 3:   log pseudolikelihood = -41835.802  

Multinomial logistic regression                 Number of obs     =     12,719
                                                Wald chi2(18)     =      10.67
                                                Prob > chi2       =     0.9079
Log pseudolikelihood = -41835.802               Pseudo R2         =     0.0006

                                     (Std. Err. adjusted for 12,335 clusters in hhid)
-------------------------------------------------------------------------------------
                    |               Robust
                 t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
0__control          |  (base outcome)
--------------------+----------------------------------------------------------------
1__ballot_secrecy   |
       d_race_black |   .0302266   .0714219     0.42   0.672    -.1097577    .1702108
        d_race_hisp |  -.0002109   .1449659    -0.00   0.999    -.2843387     .283917
       d_race_other |    .029164   .1631496     0.18   0.858    -.2906033    .3489312
      d_gend_female |   .0479298   .0657621     0.73   0.466    -.0809615    .1768211
      d_mar_married |   .1362692   .1584792     0.86   0.390    -.1743443    .4468828
      d_mar_unknown |   .7549761   .9340738     0.81   0.419    -1.075775    2.585727
                age |    .006649   .0222018     0.30   0.765    -.0368657    .0501636
               age2 |  -.0043408   .0326538    -0.13   0.894    -.0683411    .0596595
           age_miss |  -1.100442   .8664579    -1.27   0.204    -2.798668    .5977846
              _cons |  -.1971924   .3486539    -0.57   0.572    -.8805415    .4861566
--------------------+----------------------------------------------------------------
2__personalized_url |
       d_race_black |   .0004174   .0739502     0.01   0.995    -.1445223    .1453572
        d_race_hisp |  -.0244353   .1506358    -0.16   0.871    -.3196761    .2708055
       d_race_other |   .0599449   .1688205     0.36   0.723    -.2709372    .3908269
      d_gend_female |   .0604379   .0682051     0.89   0.376    -.0732416    .1941174
      d_mar_married |   .0970111   .1636391     0.59   0.553    -.2237156    .4177378
      d_mar_unknown |   1.232841   1.054476     1.17   0.242    -.8338933    3.299576
                age |  -.0139141   .0230481    -0.60   0.546    -.0590875    .0312593
               age2 |   .0246266    .033894     0.73   0.467    -.0418044    .0910576
           age_miss |  -1.369872   .9925244    -1.38   0.168    -3.315184    .5754405
              _cons |   .1369933   .3617682     0.38   0.705    -.5720593     .846046
-------------------------------------------------------------------------------------

 ( 1)  [0__control]o.d_race_black = 0
 ( 2)  [1__ballot_secrecy]d_race_black = 0
 ( 3)  [2__personalized_url]d_race_black = 0
 ( 4)  [0__control]o.d_race_hisp = 0
 ( 5)  [1__ballot_secrecy]d_race_hisp = 0
 ( 6)  [2__personalized_url]d_race_hisp = 0
 ( 7)  [0__control]o.d_race_other = 0
 ( 8)  [1__ballot_secrecy]d_race_other = 0
 ( 9)  [2__personalized_url]d_race_other = 0
 (10)  [0__control]o.d_gend_female = 0
 (11)  [1__ballot_secrecy]d_gend_female = 0
 (12)  [2__personalized_url]d_gend_female = 0
 (13)  [0__control]o.d_mar_married = 0
 (14)  [1__ballot_secrecy]d_mar_married = 0
 (15)  [2__personalized_url]d_mar_married = 0
 (16)  [0__control]o.d_mar_unknown = 0
 (17)  [1__ballot_secrecy]d_mar_unknown = 0
 (18)  [2__personalized_url]d_mar_unknown = 0
 (19)  [0__control]o.age = 0
 (20)  [1__ballot_secrecy]age = 0
 (21)  [2__personalized_url]age = 0
 (22)  [0__control]o.age2 = 0
 (23)  [1__ballot_secrecy]age2 = 0
 (24)  [2__personalized_url]age2 = 0
 (25)  [0__control]o.age_miss = 0
 (26)  [1__ballot_secrecy]age_miss = 0
 (27)  [2__personalized_url]age_miss = 0
       Constraint 1 dropped
       Constraint 4 dropped
       Constraint 7 dropped
       Constraint 10 dropped
       Constraint 13 dropped
       Constraint 16 dropped
       Constraint 19 dropped
       Constraint 22 dropped
       Constraint 25 dropped

           chi2( 18) =   10.67
         Prob > chi2 =    0.9079

note: d_mar_unknown omitted because of collinearity
note: age_miss omitted because of collinearity
Iteration 0:   log pseudolikelihood = -2416.8423  
Iteration 1:   log pseudolikelihood = -2391.4602  
Iteration 2:   log pseudolikelihood = -2391.4545  
Iteration 3:   log pseudolikelihood = -2391.4545  

Logistic regression                             Number of obs     =      1,746
                                                Wald chi2(7)      =       8.76
                                                Prob > chi2       =     0.2704
Log pseudolikelihood = -2391.4545               Pseudo R2         =     0.0105

                                (Std. Err. adjusted for 1,701 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
           t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 d_race_black |   .0056938   .2018553     0.03   0.977    -.3899353    .4013228
  d_race_hisp |   .3428959   .4369418     0.78   0.433    -.5134943    1.199286
 d_race_other |  -.2061485   .3650728    -0.56   0.572    -.9216781    .5093811
d_gend_female |  -.4096782   .1824692    -2.25   0.025    -.7673111   -.0520452
d_mar_married |  -.1940142   .3017318    -0.64   0.520    -.7853977    .3973693
d_mar_unknown |          0  (omitted)
          age |   -.093145   .1981236    -0.47   0.638    -.4814602    .2951701
         age2 |   .0832237   .1497995     0.56   0.579     -.210378    .3768254
     age_miss |          0  (omitted)
        _cons |   2.807144   6.503594     0.43   0.666    -9.939666    15.55395
-------------------------------------------------------------------------------

 ( 1)  [t3]d_race_black = 0
 ( 2)  [t3]d_race_hisp = 0
 ( 3)  [t3]d_race_other = 0
 ( 4)  [t3]d_gend_female = 0
 ( 5)  [t3]d_mar_married = 0
 ( 6)  [t3]age = 0
 ( 7)  [t3]age2 = 0

           chi2(  7) =    8.76
         Prob > chi2 =    0.2704

note: d_mar_unknown omitted because of collinearity
Iteration 0:   log pseudolikelihood = -130966.39  
Iteration 1:   log pseudolikelihood =  -130926.4  
Iteration 2:   log pseudolikelihood = -130926.07  
Iteration 3:   log pseudolikelihood = -130926.07  

Multinomial logistic regression                 Number of obs     =     39,712
                                                Wald chi2(16)     =      14.03
                                                Prob > chi2       =     0.5963
Log pseudolikelihood = -130926.07               Pseudo R2         =     0.0003

                                     (Std. Err. adjusted for 38,191 clusters in hhid)
-------------------------------------------------------------------------------------
                    |               Robust
                 t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
0__control          |  (base outcome)
--------------------+----------------------------------------------------------------
1__ballot_secrecy   |
       d_race_black |   .0321862   .0525051     0.61   0.540    -.0707219    .1350942
        d_race_hisp |    .008722   .0901479     0.10   0.923    -.1679646    .1854087
       d_race_other |  -.1150576   .0753272    -1.53   0.127    -.2626963     .032581
      d_gend_female |  -.0138732   .0371914    -0.37   0.709     -.086767    .0590206
      d_mar_married |    .092531    .073068     1.27   0.205    -.0506796    .2357416
      d_mar_unknown |          0  (omitted)
                age |  -.0115962   .0131795    -0.88   0.379    -.0374274    .0142351
               age2 |   .0188427   .0195204     0.97   0.334    -.0194167     .057102
           age_miss |   .3223265   1.064528     0.30   0.762    -1.764109    2.408762
              _cons |    .163228   .2041636     0.80   0.424    -.2369252    .5633813
--------------------+----------------------------------------------------------------
2__personalized_url |
       d_race_black |  -.0130529   .0544699    -0.24   0.811    -.1198119    .0937061
        d_race_hisp |   .0564912   .0929628     0.61   0.543    -.1257127     .238695
       d_race_other |  -.1451731   .0782915    -1.85   0.064    -.2986216    .0082755
      d_gend_female |  -.0295227   .0385496    -0.77   0.444    -.1050785    .0460331
      d_mar_married |   .1068253    .075201     1.42   0.155    -.0405659    .2542164
      d_mar_unknown |          0  (omitted)
                age |  -.0136827   .0136416    -1.00   0.316    -.0404197    .0130543
               age2 |    .023774   .0201839     1.18   0.239    -.0157858    .0633338
           age_miss |  -1.344346   1.416702    -0.95   0.343    -4.121032    1.432339
              _cons |   .1936382   .2114243     0.92   0.360    -.2207458    .6080221
-------------------------------------------------------------------------------------

 ( 1)  [0__control]o.d_race_black = 0
 ( 2)  [1__ballot_secrecy]d_race_black = 0
 ( 3)  [2__personalized_url]d_race_black = 0
 ( 4)  [0__control]o.d_race_hisp = 0
 ( 5)  [1__ballot_secrecy]d_race_hisp = 0
 ( 6)  [2__personalized_url]d_race_hisp = 0
 ( 7)  [0__control]o.d_race_other = 0
 ( 8)  [1__ballot_secrecy]d_race_other = 0
 ( 9)  [2__personalized_url]d_race_other = 0
 (10)  [0__control]o.d_gend_female = 0
 (11)  [1__ballot_secrecy]d_gend_female = 0
 (12)  [2__personalized_url]d_gend_female = 0
 (13)  [0__control]o.d_mar_married = 0
 (14)  [1__ballot_secrecy]d_mar_married = 0
 (15)  [2__personalized_url]d_mar_married = 0
 (16)  [0__control]o.age = 0
 (17)  [1__ballot_secrecy]age = 0
 (18)  [2__personalized_url]age = 0
 (19)  [0__control]o.age2 = 0
 (20)  [1__ballot_secrecy]age2 = 0
 (21)  [2__personalized_url]age2 = 0
 (22)  [0__control]o.age_miss = 0
 (23)  [1__ballot_secrecy]age_miss = 0
 (24)  [2__personalized_url]age_miss = 0
       Constraint 1 dropped
       Constraint 4 dropped
       Constraint 7 dropped
       Constraint 10 dropped
       Constraint 13 dropped
       Constraint 16 dropped
       Constraint 19 dropped
       Constraint 22 dropped

           chi2( 16) =   14.03
         Prob > chi2 =    0.5963

note: d_mar_unknown omitted because of collinearity
note: age_miss omitted because of collinearity
Iteration 0:   log pseudolikelihood = -4812.0325  
Iteration 1:   log pseudolikelihood =  -4789.598  
Iteration 2:   log pseudolikelihood = -4789.5951  
Iteration 3:   log pseudolikelihood = -4789.5951  

Logistic regression                             Number of obs     =      3,468
                                                Wald chi2(7)      =       8.63
                                                Prob > chi2       =     0.2806
Log pseudolikelihood = -4789.5951               Pseudo R2         =     0.0047

                                (Std. Err. adjusted for 3,415 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
           t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 d_race_black |  -.0774612   .1672807    -0.46   0.643    -.4053253    .2504029
  d_race_hisp |  -.1057197   .2652142    -0.40   0.690      -.62553    .4140906
 d_race_other |  -.3465626   .2000855    -1.73   0.083     -.738723    .0455977
d_gend_female |  -.3539265   .1761311    -2.01   0.044    -.6991371   -.0087159
d_mar_married |    .162694   .2720115     0.60   0.550    -.3704389    .6958268
d_mar_unknown |          0  (omitted)
          age |  -.1029722   .1075552    -0.96   0.338    -.3137765    .1078321
         age2 |   .0833921   .0790386     1.06   0.291    -.0715206    .2383049
     age_miss |          0  (omitted)
        _cons |   3.470787   3.618023     0.96   0.337    -3.620407    10.56198
-------------------------------------------------------------------------------

 ( 1)  [t3]d_race_black = 0
 ( 2)  [t3]d_race_hisp = 0
 ( 3)  [t3]d_race_other = 0
 ( 4)  [t3]d_gend_female = 0
 ( 5)  [t3]d_mar_married = 0
 ( 6)  [t3]age = 0
 ( 7)  [t3]age2 = 0

           chi2(  7) =    8.63
         Prob > chi2 =    0.2806

note: d_mar_unknown omitted because of collinearity
Iteration 0:   log pseudolikelihood = -99917.044  
Iteration 1:   log pseudolikelihood = -99897.121  
Iteration 2:   log pseudolikelihood =  -99897.12  

Multinomial logistic regression                 Number of obs     =     30,304
                                                Wald chi2(14)     =       6.43
                                                Prob > chi2       =     0.9544
Log pseudolikelihood =  -99897.12               Pseudo R2         =     0.0002

                                     (Std. Err. adjusted for 29,308 clusters in hhid)
-------------------------------------------------------------------------------------
                    |               Robust
                 t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
0__control          |  (base outcome)
--------------------+----------------------------------------------------------------
1__ballot_secrecy   |
       d_race_black |   .0188934   .0500325     0.38   0.706    -.0791685    .1169553
        d_race_hisp |   .0824727   .0730251     1.13   0.259    -.0606538    .2255992
       d_race_other |     .09167   .0961224     0.95   0.340    -.0967265    .2800665
      d_mar_married |  -.0712932   .0925278    -0.77   0.441    -.2526445     .110058
      d_mar_unknown |          0  (omitted)
                age |   .0134802   .0128214     1.05   0.293    -.0116494    .0386097
               age2 |  -.0186857   .0192025    -0.97   0.331    -.0563219    .0189504
      d_gend_female |   .0332205   .0416851     0.80   0.425    -.0484808    .1149219
              _cons |  -.2393915   .1880681    -1.27   0.203    -.6079982    .1292152
--------------------+----------------------------------------------------------------
2__personalized_url |
       d_race_black |   .0256467   .0517664     0.50   0.620    -.0758136    .1271071
        d_race_hisp |   .0753062   .0754913     1.00   0.318    -.0726541    .2232665
       d_race_other |   .0358533    .099811     0.36   0.719    -.1597726    .2314793
      d_mar_married |  -.0764207   .0958596    -0.80   0.425    -.2643021    .1114606
      d_mar_unknown |          0  (omitted)
                age |   .0132214   .0134212     0.99   0.325    -.0130837    .0395264
               age2 |  -.0163031   .0201334    -0.81   0.418    -.0557637    .0231575
      d_gend_female |   .0218741   .0431198     0.51   0.612    -.0626391    .1063873
              _cons |  -.2372528   .1964804    -1.21   0.227    -.6223473    .1478417
-------------------------------------------------------------------------------------

 ( 1)  [0__control]o.d_race_black = 0
 ( 2)  [1__ballot_secrecy]d_race_black = 0
 ( 3)  [2__personalized_url]d_race_black = 0
 ( 4)  [0__control]o.d_race_hisp = 0
 ( 5)  [1__ballot_secrecy]d_race_hisp = 0
 ( 6)  [2__personalized_url]d_race_hisp = 0
 ( 7)  [0__control]o.d_race_other = 0
 ( 8)  [1__ballot_secrecy]d_race_other = 0
 ( 9)  [2__personalized_url]d_race_other = 0
 (10)  [0__control]o.d_mar_married = 0
 (11)  [1__ballot_secrecy]d_mar_married = 0
 (12)  [2__personalized_url]d_mar_married = 0
 (13)  [0__control]o.age = 0
 (14)  [1__ballot_secrecy]age = 0
 (15)  [2__personalized_url]age = 0
 (16)  [0__control]o.age2 = 0
 (17)  [1__ballot_secrecy]age2 = 0
 (18)  [2__personalized_url]age2 = 0
 (19)  [0__control]o.d_gend_female = 0
 (20)  [1__ballot_secrecy]d_gend_female = 0
 (21)  [2__personalized_url]d_gend_female = 0
       Constraint 1 dropped
       Constraint 4 dropped
       Constraint 7 dropped
       Constraint 10 dropped
       Constraint 13 dropped
       Constraint 16 dropped
       Constraint 19 dropped

           chi2( 14) =    6.43
         Prob > chi2 =    0.9544

note: d_mar_unknown omitted because of collinearity
note: age_miss omitted because of collinearity
Iteration 0:   log pseudolikelihood =  -4355.194  
Iteration 1:   log pseudolikelihood = -4335.7924  
Iteration 2:   log pseudolikelihood = -4335.7908  
Iteration 3:   log pseudolikelihood = -4335.7908  

Logistic regression                             Number of obs     =      3,146
                                                Wald chi2(7)      =       6.82
                                                Prob > chi2       =     0.4481
Log pseudolikelihood = -4335.7908               Pseudo R2         =     0.0045

                                (Std. Err. adjusted for 3,066 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
           t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 d_race_black |   -.220906   .1582183    -1.40   0.163    -.5310081    .0891961
  d_race_hisp |   .2345483    .247366     0.95   0.343    -.2502802    .7193767
 d_race_other |  -.0116692   .2484156    -0.05   0.963    -.4985548    .4752164
d_gend_female |   -.094554   .1553903    -0.61   0.543    -.3991135    .2100055
d_mar_married |  -.0514019   .2129962    -0.24   0.809    -.4688667     .366063
d_mar_unknown |          0  (omitted)
          age |   .1217937   .1068316     1.14   0.254    -.0875924    .3311798
         age2 |  -.0926407   .0775599    -1.19   0.232    -.2446552    .0593739
     age_miss |          0  (omitted)
        _cons |  -3.806747   3.632508    -1.05   0.295    -10.92633    3.312839
-------------------------------------------------------------------------------

 ( 1)  [t3]d_race_black = 0
 ( 2)  [t3]d_race_hisp = 0
 ( 3)  [t3]d_race_other = 0
 ( 4)  [t3]d_gend_female = 0
 ( 5)  [t3]d_mar_married = 0
 ( 6)  [t3]age = 0
 ( 7)  [t3]age2 = 0

           chi2(  7) =    6.82
         Prob > chi2 =    0.4481

Iteration 0:   log pseudolikelihood = -453319.55  
Iteration 1:   log pseudolikelihood = -453267.69  
Iteration 2:   log pseudolikelihood = -453267.61  
Iteration 3:   log pseudolikelihood = -453267.61  

Multinomial logistic regression                 Number of obs     =    137,482
                                                Wald chi2(18)     =      15.30
                                                Prob > chi2       =     0.6415
Log pseudolikelihood = -453267.61               Pseudo R2         =     0.0001

                                    (Std. Err. adjusted for 131,071 clusters in hhid)
-------------------------------------------------------------------------------------
                    |               Robust
                 t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
0__control          |  (base outcome)
--------------------+----------------------------------------------------------------
1__ballot_secrecy   |
       d_race_black |   .0183491   .0292364     0.63   0.530    -.0389532    .0756514
        d_race_hisp |    .011098   .0239432     0.46   0.643    -.0358299    .0580259
       d_race_other |   .0052344   .0410332     0.13   0.898    -.0751891    .0856579
      d_gend_female |  -.0153561   .0200433    -0.77   0.444    -.0546402     .023928
      d_mar_married |  -.0007428   .0349074    -0.02   0.983    -.0691601    .0676744
      d_mar_unknown |  -1.200081   1.121331    -1.07   0.285    -3.397849    .9976876
                age |   .0068933   .0056356     1.22   0.221    -.0041522    .0179388
               age2 |  -.0069974   .0082429    -0.85   0.396    -.0231531    .0091584
           age_miss |   .5088053    1.04991     0.48   0.628     -1.54898    2.566591
              _cons |  -.1318562   .0866999    -1.52   0.128    -.3017849    .0380724
--------------------+----------------------------------------------------------------
2__personalized_url |
       d_race_black |   .0016962   .0302738     0.06   0.955    -.0576394    .0610318
        d_race_hisp |  -.0078278   .0247739    -0.32   0.752    -.0563838    .0407282
       d_race_other |  -.0290466   .0425388    -0.68   0.495     -.112421    .0543278
      d_gend_female |   -.015415   .0207402    -0.74   0.457     -.056065    .0252351
      d_mar_married |   -.004064   .0361218    -0.11   0.910    -.0748614    .0667334
      d_mar_unknown |  -.9207607   1.155641    -0.80   0.426    -3.185775    1.344254
                age |   .0077466   .0058735     1.32   0.187    -.0037652    .0192583
               age2 |   -.007449   .0085949    -0.87   0.386    -.0242947    .0093968
           age_miss |    .398741   1.083737     0.37   0.713    -1.725345    2.522827
              _cons |  -.1365393   .0902684    -1.51   0.130    -.3134621    .0403835
-------------------------------------------------------------------------------------

 ( 1)  [0__control]o.d_race_black = 0
 ( 2)  [1__ballot_secrecy]d_race_black = 0
 ( 3)  [2__personalized_url]d_race_black = 0
 ( 4)  [0__control]o.d_race_hisp = 0
 ( 5)  [1__ballot_secrecy]d_race_hisp = 0
 ( 6)  [2__personalized_url]d_race_hisp = 0
 ( 7)  [0__control]o.d_race_other = 0
 ( 8)  [1__ballot_secrecy]d_race_other = 0
 ( 9)  [2__personalized_url]d_race_other = 0
 (10)  [0__control]o.d_gend_female = 0
 (11)  [1__ballot_secrecy]d_gend_female = 0
 (12)  [2__personalized_url]d_gend_female = 0
 (13)  [0__control]o.d_mar_married = 0
 (14)  [1__ballot_secrecy]d_mar_married = 0
 (15)  [2__personalized_url]d_mar_married = 0
 (16)  [0__control]o.d_mar_unknown = 0
 (17)  [1__ballot_secrecy]d_mar_unknown = 0
 (18)  [2__personalized_url]d_mar_unknown = 0
 (19)  [0__control]o.age = 0
 (20)  [1__ballot_secrecy]age = 0
 (21)  [2__personalized_url]age = 0
 (22)  [0__control]o.age2 = 0
 (23)  [1__ballot_secrecy]age2 = 0
 (24)  [2__personalized_url]age2 = 0
 (25)  [0__control]o.age_miss = 0
 (26)  [1__ballot_secrecy]age_miss = 0
 (27)  [2__personalized_url]age_miss = 0
       Constraint 1 dropped
       Constraint 4 dropped
       Constraint 7 dropped
       Constraint 10 dropped
       Constraint 13 dropped
       Constraint 16 dropped
       Constraint 19 dropped
       Constraint 22 dropped
       Constraint 25 dropped

           chi2( 18) =   15.30
         Prob > chi2 =    0.6415

note: d_mar_unknown omitted because of collinearity
note: age_miss omitted because of collinearity
Iteration 0:   log pseudolikelihood = -23601.054  
Iteration 1:   log pseudolikelihood = -23589.752  
Iteration 2:   log pseudolikelihood = -23589.752  

Logistic regression                             Number of obs     =     17,023
                                                Wald chi2(7)      =       3.89
                                                Prob > chi2       =     0.7923
Log pseudolikelihood = -23589.752               Pseudo R2         =     0.0005

                               (Std. Err. adjusted for 16,496 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
           t3 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
 d_race_black |   .0388057   .0827609     0.47   0.639    -.1234026    .2010141
  d_race_hisp |  -.0228882    .072097    -0.32   0.751    -.1641958    .1184193
 d_race_other |   .0605108   .0972077     0.62   0.534    -.1300127    .2510344
d_gend_female |  -.0569998   .0578641    -0.99   0.325    -.1704114    .0564118
d_mar_married |   .0195916   .0770783     0.25   0.799    -.1314791    .1706623
d_mar_unknown |          0  (omitted)
          age |   .0472724   .0483298     0.98   0.328    -.0474523    .1419972
         age2 |  -.0333866   .0353818    -0.94   0.345    -.1027336    .0359605
     age_miss |          0  (omitted)
        _cons |  -1.610632   1.630917    -0.99   0.323     -4.80717    1.585906
-------------------------------------------------------------------------------

 ( 1)  [t3]d_race_black = 0
 ( 2)  [t3]d_race_hisp = 0
 ( 3)  [t3]d_race_other = 0
 ( 4)  [t3]d_gend_female = 0
 ( 5)  [t3]d_mar_married = 0
 ( 6)  [t3]age = 0
 ( 7)  [t3]age2 = 0

           chi2(  7) =    3.89
         Prob > chi2 =    0.7923

. 
. log close
      name:  <unnamed>
       log:  C:\Users\afang\Documents\PSRM_BallotSecrecy\PublicReplicationArchive\03_Appendix.log
  log type:  text
 closed on:  31 Mar 2017, 14:50:42
-----------------------------------------------------------------------------------------------------
